computational.science

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ML and Optimisation postdoc vacancies
by Uwe Aickelin 26 Jul '21

26 Jul '21

If you are looking for a Machine Learning / Optimisation postdoc, we have two exciting jobs for you. Please check below positions RF 4 (machine learning / optimisation) and RF 5 (uncertainty handling). You will work with a top team on a super high impact application - I can assure you our work could not be more central to current events in Australia!!! Please note, due to the urgency of the work, you must be currently located within Australia and able to commence immediately or as soon as your notice period has been served. These roles are part of a $20m Hub and more vacancies will be advertised soon. https://jobs.unimelb.edu.au/en/job/905792/research-fellows-pharma-and-food-… Please apply online – deadline 22 August 2021. Professor Uwe Aickelin | Head of School of Computing and Information Systems Faculty of Engineering and Information Technology Level 3, Melbourne Connect – 700 Swanston Street The University of Melbourne, Victoria 3010 Australia T: +61 3 8344 3635 E: uwe.aickelin(a)unimelb.edu.au<mailto:uwe.aickelin@unimelb.edu.au> http://aickelin.com/ | http://linkedin.com/in/aickelin [A close up of a sign Description automatically generated] <https://melbconnect.com.au/> [Join R U OK?Day | R U OK?] I acknowledge the Traditional Owners of the land on which I work, and pay my respects to the Elders, past and present. This email and any attachments may contain personal information or information that is otherwise confidential or the subject of copyright. Any use, disclosure or copying of any part of it is prohibited. The University does not warrant that this email or any attachments are free from viruses or defects. Please check any attachments for viruses and defects before opening them. If this email is received in error, please delete it and notify us by return email. CRICOS: 00116K

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2021 IEEE Technical Committee on Cloud Computing (TCCLD) Award Nomination
by Hojjat Baghban 25 Jul '21

25 Jul '21

*Dear Members and Friends, * As a friendly reminder, kindly please nominate qualified candidates for the* 2021 IEEE TCCLD* <https://tc.computer.org/tccld/awards/> awards listed below by August 20, 2021. Also, we truly thank you in advance to help with distributing the call for nominations. (https://tc.computer.org/tccld/awards/ ) *Call For Nominations ** 2021 IEEE Technical Committee on cloud computing (TCCLD ) Award Announcement* - - *TCCLD Outstanding Leadership Award * *This award recognizes one individual for her/his outstanding leadership contributions in the field of cloud computing. Also, the outstanding contributions in the application of cloud computing which affect and improve global business and help organizations and individuals are considered.* - *TCCLD Outstanding Service Award * *This award recognizes one individual with outstanding services to building the cloud computing community, and persistent volunteer efforts, such as services to IEEE TCCLD activities worldwide, annual related events.* - *TCCLD Women in Cloud Computing Award * *It recognizes women leaders who have made outstanding, influential, and potentially long-lasting contributions in the field of cloud computing and solve real problems. * - *TCCLD Impact Award * *It recognizes senior researchers or educators for her/his significant/distinguished contribution in the field of cloud computing.* - *TCCLD Outstanding Ph.D. Thesis Award. * TCCLD Outstanding Ph.D. thesis award is presented to a researcher whose Ph.D. thesis has the potential of a very high impact in cloud computing or gives direct evidence of such an impact. Only a Ph.D. degree obtained in 2020/2021 is considered for this award. - *TCCLD Rising Star Award (within 5 years of receiving the Ph.D. degree)* It recognizes outstanding young scientists and engineers who have demonstrated exceptional capabilities and made a significant contribution to the field of cloud computing. Only candidates who receive their Ph.D. within 5 years are eligible. - *TCCLD Research Innovation Award.* Anyone or one group of collaborators whose outstanding technical innovations are in the field of cloud computing. The contributors must have a long-term impact on advancing the theory and practice in cloud computing. - *Eligible applicants* 1. The IEEE TCCLD members. Join TCCLD Now <https://www.ieee.org/membership-catalog/productdetail/showProductDetailPage…> 2. Qualified candidates except for the IEEE TCCLD chairs, TCCLD executive committee members, and the past IEEE TCCLD awardees. 3. Nominees that have not been recognized for the TCCLD award will be reviewed with higher priority. 4. In terms of the TCCLD Outstanding Ph.D. Thesis Award, the Ph.D. degree should have been obtained in 2020/2021. - Please note: self-nomination is not permitted. *Nomination Process* - - Anyone in the field can nominate one person. Self-nominations are not accepted. - Nominations should include a proposed citation (up to 25 words), which includes the field of research/work and contributions, a detailed statement to justify the nomination (500 words or less), and personal/team web page URL of the nominee. - Two supporting letters are required for each nomination. The letters should address the significance of the contributions cited in the nomination. - Nominations that did not result in an award can be resubmitted or updated in subsequent years. - The Awards Committee will evaluate all nominations and decide on zero or more winners for each award category. *Important Dates:* - August 20, 2021: Nomination due - September 10, 2021: Selection results. (Internal) - The announcement of winners will be announced. IEEE DataCom 2021 <http://edgence.org/DATACOM2021/> *Submission Link* All nominations should be sent through the following link. All the files should be merged into one PDF file. * TCCLD Award Nomination <https://docs.google.com/forms/d/e/1FAIpQLSer9Ix6Ukue8UATIawg0cqUdBS4UxSDXNU…>* Note: If you require further information, feel free to contact ieeetccld(a)gmail.com <ieeetccld(a)gmail.com> *Awards committee chair* - *Professor Chunming Rong* <https://www.ux.uis.no/~chun/bio.html>, University of Stavanger, Norway, Email: chunming.rong(a)gmail.com Yours SIncerely, Hojjat Baghban, Ph.D. Executive Committee at IEEE Technical Committee on Cloud Computing (TCCLD), Membership Director.

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Call for Next-Generation Data Scientist Award - IEEE DSAA’2021
by ngds2021＠dsaa.co 23 Jul '21

23 Jul '21

Next Generation Data Scientist Award (NGDS Award) by IEEE International Conference on Data Science and Advanced Analytics (DSAA, CORE-A ranked) https://dsaa2021.dcc.fc.up.pt/ ** Deadline: 31 August 2021 The IEEE International Conference on Data Science and Advanced Analytics (DSAA) will offer a limited number (or none) of NGDS Awards every year to early‐career researchers (ECR) who have got PhD degrees within five years in data science. The NGDS Award has been the first and only global initiative to support the production and certification of qualified next‐generation data scientists. The NGDS awards will be sponsored by some of the DSAA sponsors. Each NGDS awardee will receive USD 1,000. One of the critical challenges facing the era of data science lies in the significant gap between the increasing data scientist job demand and the limited availability of qualified data scientists. The purpose of offering this NGDS award is to encourage young talents to conduct significant foundational research and applied innovation in Data Science toward a profound and world-standard level. All ECRs with the papers accepted at previous and current DSAA conferences are invited to apply, although the awards open to all applicants in data science. ** Selection Criteria of NGDS The DSAA steering committee sets up the NGDS Award to be highly prestigious and selective. Hence, the criteria for NGDS candidate selection are rigorous. This may involve the following aspects: -- PhD qualification in data science including statistics, machine learning, artificial intelligence, and other related fields; -- A strong track record in terms of theoretical contributions, business impact and/or educational contributions, which are quantifiable and outstanding; -- A reachable five-year career plan for significantly contributing to the data science community in terms of research, innovation, applications and/or education; -- Strong referee reports from two recognized data scientists; -- Strong recommendation from the candidate’s department or supervisor. ** How to Submit An NGDS Award Application? The deadline for applications is 31 August 2021. Applicants are encouraged to attend IEEE DSAA’2021 which will be held on 6-9 Oct 2021 in Porto, Portugal. An NGDS award candidate should submit an application to the NGDS award chairs, which includes: -- NGDS Award Application Form (download the NGDS application form from here) to address: dsaa2021(a)dsaa.co -- Applicant information; -- Response to the above selection criteria; -- Title, authors and track record of DSAA publications and attendance; -- Resume with affiliation, education background, publications, projects, cases of impact, awards etc.; -- Certificate showing staff ID and working status; -- Two referee reports with referee’s contact details and signatures; -- A recommendation letter from head of department or supervisor on the organization letterhead. -- All application materials should be zipped into a file titled “2021_NGDS_Applicant Last Name_ First Name.zip” and submitted to dsaa2021(a)dsaa.co. Successful candidates must register and attend DSAA’2021, otherwise, the award may be given to other candidates in the shortlist list per the selection committee’s decision. An announcement of the final winner will be made in the DSAA’2021 conference banquet. All documents should be in PDF and attached to the email. Late submissions, or documents in other formats will not be accepted. ** Contacts -- Any inquiries and questions should be addressed to dsaa2021(a)dsaa.co. -- More information and registration to DSAA’2021 is available here: https://dsaa2021.dcc.fc.up.pt/attending/registration. -- The list of existing NGDS Awardees is available at DSAA Awards webpage (https://dsaa.co/?page_id=1583).

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CFP - Special Session on High Performance Computing in Modelling and Simulation (HPCMS) - Valladolid (Spain)
by William Spataro 22 Jul '21

22 Jul '21

(sorry for cross postings) ************************************************************************** CALL FOR PAPERS: Special Session on High Performance Computing in Modelling and Simulation (HPCMS) Within PDP 2022 (pdp2022.infor.uva.es) The 30th Euromicro International Conference on Parallel, and Network-Based Computing Valladolid (Spain) (hybrid attendance) 9-11 March 2022 https://pdp2022.infor.uva.es/specialsessions/hpcms/hpcms.php Deadline: September 30th, 2021 Contact: William Spataro - spataro(a)unical.it ************************************************************************* AIMS AND SCOPE The development of models through which computers can simulate the evolution of artificial and natural systems is fundamental for the advancement of Science. In the last decades, the increasing power of computers has allowed to considerably extend the application of computing methodologies in research and industry, but also to the quantitative study of complex phenomena. This has permitted a broad application of numerical methods for differential equation systems (e.g., FEM, FDM, etc.) on one hand, and the application of alternative computational paradigms, such as Cellular Automata, Genetic Algorithms, Neural networks, Swarm Intelligence, etc., on the other. These latter have demonstrated their effectiveness for modelling purposes when traditional simulation methodologies have proven to be impracticable. Following the success of our past HPCMS workshops at PDP (since 2014), we are glad to invite you to our eighth edition which will take place in Valladolid (Spain). An important mission of the HPCMS Workshop is to provide a platform for a multidisciplinary community composed of scholars, researchers, developers, educators, practitioners and experts from world leading Universities, Institutions, Agencies and Companies in Computational Science, and thus in the High Performance Computing for Modelling and Simulation field. HPCMS intent is to offer an opportunity to express and confront views on trends, challenges, and state-of-the art in diverse application fields, such as engineering, physics, chemistry, biology, geology, medicine, ecology, sociology, traffic control, economy, etc. Topics of interest include, but are not limited to, the following: - High-performance computing in computational science: intra-disciplinary and multi-disciplinary research applications - Complex systems modelling and simulation - Cellular Automata, Genetic Algorithms, Neural networks, Swarm Intelligence implementations - Integrated approach to optimization and simulation - MPI, OpenMP, GPGPU applications in Computational Science - Optimization algorithms, modelling techniques related to optimization in Computational Science - High-performance Software developed to solve science (e.g., biological, physical, and social), engineering, medicine, and humanities problems - Hardware approaches of high performance computing in modeling and simulation IMPORTANT DATES Paper submission: 30 September 2021 Acceptance notification: 22 December 2021 Camera ready due: 16 January 2022 Conference: 9 - 11 March 2022 Submission guidelines Prospective authors should submit a full paper not exceeding 8 pages in the IEEE Conference proceedings format (IEEEtran, double-column, 10pt). Double-bind review: the first page of the paper should contain only the title and abstract; in the reference list, references to the authors own work should appear as "omitted for blind review" entries. For submission, please use the following link and select the HPCMS session: https://easychair.org/my/conference?conf=pdp2022 and select the "High Performance Computing in Modelling and Simulation" track. Manuscript submission Publication All accepted papers will be included in the same volume, published by the Conference Publishing Services (CPS). The Final Paper Preparation and Submission Instructions will be published after the notification of acceptance. Authors of accepted papers are expected to register and present their papers at the Conference. Conference proceedings will be submitted for inclusion in Xplore and the CSDL, and for indexing, among others, to DBLP, Scopus ScienceDirect, and ISI Web of Knowledge. Special Issue As for previous editions, organizers of the HPCMS session are planning a Special Issue of an important international ISI Journal, based on distinguished papers that will be accepted for the session. Organizers William Spataro - University of Calabria, Italy Georgios Sirakoulis - Democritus University of Thrace, Greece Giuseppe A. Trunfio - University of Sassari, Italy Rocco Rongo, University of Calabria, Italy Andrea Giordano, ICAR-CNR, Italy Program Committee Angelos Amanatiadis, Democritus University of Thrace, Greece Donato D'Ambrosio, University of Calabria, Italy Pawel Topa, AGH University of Science and Technology, Poland Gianluigi Folino, ICAR-CNR, Italy Lou D'Alotto, York College/CUNY, New York, USA Antonios Gasteratos, Democritus University of Thrace, Greece Ioakeim Georgoudas, Democritus University of Thrace, Greece Marco Beccutti, University of Torino, Italy Rolf Hoffmann, Darmstadt University, Germany Ioannis Karafyllidis, Democritus University of Thrace, Greece Yaroslav Sergeyev, University of Calabria, Italy Antisthenis Tsompanas, University of the West of England, UK Rocco Rongo, University of Calabria, Italy Georgios Sirakoulis, Democritus University of Thrace, Greece William Spataro, University of Calabria, Italy Giuseppe A. Trunfio, University of Sassari, Italy Marco Villani, University of Modena and Reggio Emilia, Italy Jaroslaw Was, AGH University of Science and Technology, Poland Davide Spataro, Degiro, The Netherlands Massimo Cafaro, University of Salento, Italy Andrea Giordano, ICAR-CNR, Italy Mario Cannataro, University Magna Graecia of Catanzaro, Italy Gihan R. Mudalige, University of Warwick, UK Alessio De Rango, University of Calabria, Italy -- °-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-° William Spataro Department of Mathematics & Computer Science High Performance Computing Center University of Calabria I-87036 Arcavacata di Rende (CS) Italy Phone(s) : +39.0984.496464 Fax : +39.0984.493570 Web: www.mat.unical.it/spataro Email: spataro(a)unical.it -°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-°-° -- ------------------------------------------------------------------------------------------------------------------ Il banner è generato automaticamente dal servizio di posta elettronica dell'Università della Calabria <http://www.unical.it/5x1000>

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Invitation to join 2021 Summer Short Course 'Deep Learning and Computer Vision', 23-24th August 2021
by Ioanna Koroni 21 Jul '21

21 Jul '21

Dear Machine Learning and Deep Neural Networks engineers, scientists and enthusiasts, you are welcomed to register in the CVML Short e-course on 'Deep Learning and Computer Vision', 23-24th August 2021: http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vi sion-for-autonomous-systems-2021/ It will take place as a two-day e-course (due to COVID-19 circumstances), hosted by the Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece, providing a series of live lectures delivered through a tele-education platform (Zoom). They will be complemented with on-line video recorded lectures and lecture pdfs, to facilitate international participants having time difference issues and to enable you to study at own pace. You can also self-assess your knowledge, by filling appropriate questionnaires (one per lecture). You will be provided programming to improve your programming skills. You will also have accesses to tutorial exercises to better your theoretical understanding of selected CVML topics. This 6th edition of this course is part of the very successful CVML short course series that took place in the last four years. Course description 'Deep Learning and Computer Vision' The short e-course consists of 16 1-hour live lectures organized in two Parts (1 Part per day): Part A lectures (8 hours) provide an in-depth presentation to autonomous systems imaging and the relevant architectures as well as a solid background on the necessary topics of computer vision (Image acquisition, camera geometry, Stereo and Multiview imaging, Mapping and Localization) and machine learning (Introduction to neural networks, Perceptron, backpropagation, Deep neural networks, Convolutional NNs). Part B lectures (8 hours) provide in-depth views of the various topics encountered in autonomous systems perception, ranging from vehicle localization and mapping, to Neural SLAM, target detection and tracking. Part B also contains application-oriented lectures on autonomous drones, cars and marine vessels, e.g., drone mission planning for cinematography and related applications (marine surveillance, infrastructure/building inspection, car vision). Course lectures Part A: (first day, 8 lectures) 1. Introduction to autonomous systems imaging 2. <http://icarus.csd.auth.gr/digital-image-and-videos> Digital Image and Videos 3. <http://icarus.csd.auth.gr/camera-geometry/> Camera geometry 4. <http://icarus.csd.auth.gr/stereo-and-multiview-imaging-lecture> Stereo and Multiview imaging 5. <http://icarus.csd.auth.gr/artificial-neural-networks-perceptron-lecture> Introduction to Artificial Neural Networks. Perceptron 6. <http://icarus.csd.auth.gr/multilayer-perceptron-backpropagation-lecture> Multilayer perceptron. Backpropagation 7. Deep neural networks. <http://icarus.csd.auth.gr/convolutional-neural-networks-lecture> Convolutional NNs 8. Introduction to multiple drone imaging Part B: (second day, 8 lectures) 1. <http://icarus.csd.auth.gr/3d-robot-localization-and-mapping-lecture> Simultaneous Localization and Mapping 2. <http://icarus.csd.auth.gr/neural-slam-lecture/> Neural Slam 3. <http://icarus.csd.auth.gr/deep-object-detection-lecture> Deep Object Detection 4. 2D Visual Object Tracking 5. Drone mission planning and control 6. Introduction to car vision 7. Introduction to autonomous marine vehicles 8. CVML Software Development Tools Though independent, the attendees of this short e-course will greatly benefit by attending the CVML Short e-course on 'Computer Vision for Autonomous Systems' 25-27th August 2021: http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep -learning-and-computer-vision-for-autonomous-systems-2021/ You can use the following link for course registration: http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vi sion-for-autonomous-systems-2021/ Lecture topics, sample lecture ppts and videos, self-assessment questionnaires, programming exercises and tutorial exercises can be found therein. For questions, please contact: Ioanna Koroni <koroniioanna(a)csd.auth.gr <mailto:koroniioanna@csd.auth.gr> > The short course is organized by Prof. I. Pitas, IEEE and EURASIP fellow and IEEE distinguished speaker. He is the coordinator of the EC funded International AI Doctoral Academy (AIDA <http://www.i-aida.org/> ), that is co-sponsored by all 5 European AI R&D flagship projects (H2020 ICT48). He was initiator and first Chair of the IEEE SPS Autonomous Systems Initiative. He is Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece. He was Coordinator of the European Horizon2020 R&D project Multidrone. He is ranked 249-top Computer Science and Electronics scientist internationally by Guide2research (2018). He has 33800+ citations to his work and h-index 86+. AUTH is ranked 153/182 internationally in Computer Science/Engineering, respectively, in USNews ranking. Relevant links: 1) Prof. I. Pitas: https://scholar.google.gr/citations?user=lWmGADwAAAAJ <https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el> &hl=el 2) Horizon2020 EU funded R&D project Aerial-Core: https://aerial-core.eu/ 3) Horizon2020 EU funded R&D project Multidrone: https://multidrone.eu/ 4) International AI Doctoral Academy (AIDA): http://www.i-aida.org/ 5) Horizon2020 EU funded R&D project AI4Media: https://ai4media.eu/ 6) AIIA Lab: https://aiia.csd.auth.gr/ Sincerely yours Prof. I. Pitas Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab) Aristotle University of Thessaloniki, Greece Post scriptum: To stay current on CVML matters, you may want to register in the CVML email list, following instructions in: https://lists.auth.gr/sympa/info/cvml -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus

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[Final Paper Deadline in less than 1 Week] - IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2021
by Sanmukh Kuppannagari 10 Jul '21

10 Jul '21

********************************************************************** We apologize if you received multiple copies of this email. Please feel free to distribute it to those who might be interested ********************************************************************** Final Paper Submission deadline for the IEEE International Conference on High Performance Computing, Data, Analytics, and Data Science, HiPC 2021 is in less than one week. Please submit your papers before the deadline. Please note that this is a hard deadline and no further extension will be granted. Paper Submission Deadline: 16 July, 2021 (hard deadline) More information can be found at the call for papers: https://hipc.org/call-for-papers/ Regards, Sanmukh Kuppannagari Senior Research Associate University of Southern California https://sanmukh.github.io/

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[CFP]13th Int. Conf. on on Neural Computation Theory and Applications :: New Late-Breaking Deadline - July 23rd
by Alessio Martino 09 Jul '21

09 Jul '21

CALL FOR PAPERS 13th International Conference on Neural Computation Theory and Applications New Late-Breaking Submission Deadline: July 23, 2021 http://www.ncta.ijcci.org/ <http://www.ncta.ijcci.org/> October 25 - 27, 2021 Online Streaming In Cooperation with Spanish Association of Artificial Intelligence Association for the Advancement of Artificial Intelligence Associazione Italiana per l'Intelligenza Artificiale Neural computation and artificial neural networks, especially in relation to deep learning, have seen an explosion of interest over the recent decades, and are being successfully applied across an extraordinary range of problem domains, in areas as diverse as finance, medicine, engineering, geology and physics, in problems of complex dynamics and complex behavior prediction, classification or control. Several architectures, learning strategies and algorithms have been introduced in this highly dynamic field in the last couple of decades. Nowadays, having reached notable scientific and applicative maturity, neural computation and related techniques are considered as major basis toward the completion of intelligent artificial systems. This conference intends to be a major forum for scientists, engineers and practitioners interested in the study, analysis, design, modeling and implementation of neural computing systems, both theoretically and in a broad range of application fields. Conference Chair(s) Juan Julian Merelo, University of Granada, Spain Kevin Warwick (honorary), University of Reading and Coventry University, United Kingdom Program Chair(s) H. K. Lam, King's College London, United Kingdom Marie Cottrell, Université Paris1, France With the presence of internationally distinguished keynote speakers: Susana Vieira, University of Lisbon, Portugal Joseph Rynkiewicz, Université de Paris 1 Panthéon-Sorbonne, France Carlos Coello, CINVESTAV-IPN, Mexico Barbara Hammer, Bielefeld University, Germany Proceedings will be submitted for indexation by: SCOPUS, Google Scholar, The DBLP Computer Science Bibliography, Semantic Scholar, Microsoft Academic, Engineering Index (EI), Web of Science / Conference Proceedings Citation Index. A short list of presented papers will be selected so that revised and extended versions of these papers will be published by Springer in a SCI Series book. All papers presented at the conference venue will also be available at the SCITEPRESS Digital Library. Also, a short list of best papers will be invited for a post-conference special issue of the Springer Nature Computer Science journal. Kind regards, Mónica Saramago NCTA Secretariat Web: http://www.ncta.ijcci.org/ <http://www.ncta.ijcci.org/> e-mail: ncta.secretariat(a)insticc.org <mailto:ncta.secretariat@insticc.org> ________________________________________ Alessio Martino, PhD, Research Fellow Italian National Research Council Institute of Cognitive Sciences and Technologies (ISTC-CNR) Via San Martino della Battaglia 44, 00185 Rome, Italy <https://www.google.com/maps/place/Via+S.+Martino+della+Battaglia,+44,+00185…> Phone: (+39)0644362370-5 E-mail: alessio.martino(a)istc.cnr.it <mailto:alessio.martino@istc.cnr.it> Web: www.istc.cnr.it/en <http://www.istc.cnr.it/en>

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Invitation for the 2021 Summer e-School on Deep Learning and Computer Vision, 23-27th August 2021, Aristotle University of Thessaloniki, Thessaloniki, Greece
by Ioanna Koroni 07 Jul '21

07 Jul '21

Dear Machine Learning, Computer Vision and Autonomous Systems engineers, scientists, and enthusiasts, you are welcomed to register to the 2021 Summer e-School on Deep Learning and Computer Vision: <http://icarus.csd.auth.gr/aiia-summer-school-on-autonomous-systems-2021/> http://icarus.csd.auth.gr/aiia-summer-school-on-autonomous-systems-2021/ It will take place on 23-27/08/2021 and will be hosted by the Artificial Intelligence and Information Analysis (AIIA) Lab, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece. The summer e-school consists of two short e-courses: a) 'Short Course Computer Vision and Deep Learning 2021', 23-24th August 2021, having focus on autonomous drones, cars and marine vessels: <http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-v ision-for-autonomous-systems-2021/> http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vi sion-for-autonomous-systems-2021/ b) 'Programming short course and workshop on Deep Learning and Computer Vision 2021', 25-27th August 2021, with applications in digital media and autonomous drones: <http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-dee p-learning-and-computer-vision-for-autonomous-systems-2021/> http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep -learning-and-computer-vision-for-autonomous-systems-2021/ You can follow the above-mentioned links for registration on either or both e-courses. For questions, please contact: Ioanna Koroni < <mailto:koroniioanna@csd.auth.gr> koroniioanna(a)csd.auth.gr> The first e-course contains 16 live (and recorded) lectures providing an in-depth presentation of computer vision and deep learning problems algorithms with applications on autonomous drones, cars and marine vessels. The second programming short e-course and workshop offers a mix of live (and recorded) lectures and programming workshops (hands-on lab exercises) and aims at developing registrants' programming skills for Deep Learning and Computer Vision, with focus on drone imaging/cinematography and digital media applications. Both short e-courses are organized by Prof. I. Pitas, IEEE and EURASIP fellow, He is AUTH prime investigation for H2020 project AerialCore, Coordinator of the European Horizon2020 R&D project Multidrone, Director of the Artificial Intelligence and Information analysis Lab (AIIA Lab), Aristotle University of Thessaloniki, Greece and Chair of the IEEE SPS Autonomous Systems Initiative. He is ranked 249 top Computer Science and Electronics Scientist internationally by Guide2research (2018). Aristotle University of Thessaloniki is the biggest University in Greece and in SE Europe. It is highly ranked internationally. Relevant links: 1. European Horizon2020 R&D projects Aerial-Core: <https://aerial-core.eu/> https://aerial-core.eu/, Multidrone: <https://multidrone.eu/> https://multidrone.eu/, AI4Media: <https://ai4media.eu/> https://ai4media.eu/ 2. AIIA Lab: <http://www.aiia.csd.auth.gr/> http://www.aiia.csd.auth.gr/ 3. Prof. I. Pitas: <https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el> https://scholar.google.gr/citations?user=lWmGADwAAAAJ&hl=el Course descriptions a) 'Short Course Computer Vision and Deep Learning 2021', 23-24th August 2021. <http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-v ision-for-autonomous-systems-2021/> http://icarus.csd.auth.gr/cvml-short-course-on-deep-learning-and-computer-vi sion-for-autonomous-systems-2021/ Part A (8 hours), Computer vision topic list 1. Introduction to autonomous systems imaging 2. Digital Image and Videos 3. Camera geometry 4. Stereo and Multiview imaging 5. Introduction to Artificial Neural Networks. Perceptron 6. Multilayer perceptron. Backpropagation 7. Deep neural networks. Convolutional NNs 8. Introduction to multiple drone imaging Part B (8 hours) Deep learning topic list 1. Simultaneous Localization and Mapping 2. Neural Slam 3. Deep object detection 4. 2D Visual Object Tracking 5. Drone mission planning and control 6. Introduction to car vision 7. Introduction to autonomous marine vehicles 8. CVML Software development tools b) ''Programming short course and workshop on Deep Learning and Computer Vision 2021', 25-27th August 2021. <http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-dee p-learning-and-computer-vision-for-autonomous-systems-2021/> http://icarus.csd.auth.gr/cvml-programming-short-course-and-workshop-on-deep -learning-and-computer-vision-for-autonomous-systems-2021/ Part A (8 hours), Deep learning and GPU programming sample topic list 1. Introduction to autonomous systems 2. Deep neural networks. Convolutional NNs 3. Parallel GPU and multi-core CPU architectures - GPU programming 4. Image classification with CNNs. 5. CUDA programming Part B (8 hours), Deep Learning for Computer Vision sample topic list 1. Deep learning for object/face detection 2. 2D object tracking 3. PyTorch: Understand the core functionalities of an object detector. Training and deployment. 4. OpenCV programming for object tracking Part C (8 hours), Autonomous UAV cinematography sample topic list 1. Video summarization 2. UAV cinematography 3. Video summarization with Pytorch 4. Drone cinematography with Airsim Sincerely yours Prof. I. Pitas -- This email has been checked for viruses by Avast antivirus software. https://www.avast.com/antivirus

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Open Ph.D. Position ESR4 within the European InnoCyPES Project
by Massimo CAFARO 06 Jul '21

06 Jul '21

InnoCyPES is a project funded under H2020 Marie Skłodowska-Curie Actions, Innovative Training Networks. Within the project, there is an available position at the University of Salento, Lecce, for talented, enthusiastic, and ambitious candidates with the skills and knowledge to make excellent research and breakthroughs in the field of cyber physical energy systems. The successful ESR (Early Stage Researcher) candidate will enroll in the PhD programme in Engineering of Complex Systems and be employed for 36 months in the InnoCyPES network, consisting of 7 academic beneficiaries, 4 industrial beneficiaries, in collaboration with 10 partner organizations. InnoCyPES targets at the key bottlenecks of digital transformation of the current energy system, where the ESRs are expected to study, investigate and improve various facets of digitalized and interconnected energy systems. Supervised by a consortium of prominent and experienced academic institutions, research institutes and industrial partners, they will collaboratively develop a cutting-edge system management platform that covers the entire lifecycle of data for energy system planning, operation and maintenance, based on an understanding of the energy system as a cyber-physical system. The ESR will be enrolled in an intensive doctoral training program that is both intersectoral – involving key stakeholders – and interdisciplinary, including information science, energy systems engineering and social science. Benefits All InnoCyPES ESRs will benefit from: - Extensive training in technical and transferrable skills; - Participation to network events, workshops and conferences; - A prestigious three-year MSCA Fellowship; - A competitive salary including mobility and family allowances; - Intersectoral secondment experience. Qualifications Applicants shall have proven interest in interdisciplinary and intersectoral research, and with specific interest in the InnoCyPES research areas as evidenced by the application documents. Besides, the following requirements are to be met: 1) have obtained their Master of Science degree in Computer Science, Computer Engineering or equivalent; 2) An excellent academic record (grades of B or higher) 3) have engineering background relevant to the following areas but not limited to: distributed computing, databases, distributed data management, security and privacy; knowledge of times series storage and analysis is a plus; 4) have good command of English (minimum C1 or equivalent). Requirements The applicants must fulfill the following conditions: 1) Early stage researchers: Applicants must be early-stage researchers, which means at the date of start, be in the first four years (full-time equivalent research experience) of their research careers and have not been awarded a doctoral degree; 2) Mobility Rule: researchers must not have resided or carried out their main activity (work, studies, etc.) in the country of the host institute for more than 12 months in the 3 years immediately before the recruitment date. Compulsory national service, short stays such as holidays, and time spent as part of a procedure for obtaining refugee status under the Geneva Convention1 are not taken into account. For international European interest organisations, international organisations, the European Commission's Joint Research Centre (JRC) or an 'entity created under Union law', recruited researchers must not have spent more than 12 months in the 3 years immediately before the recruitment date at the same appointing organisation. Are you interested? If you are interested in this exciting and challenging opportunity, please apply. Applicants of any age and of any nationality are eligible. The recruitment process follows an open, transparent, impartial, equitable and merit-based procedure and the European Charter and Code of Conduct for the Recruitment of Researchers. Consortium partners Host institute - Technical University of Denmark (DTU), Denmark - University of Utrecht (UU), Netherlands - Électricité de France (EDF), France - Delft University of Technology (TUD), Netherlands - University of Salento (UNILE), Italy - Norwegian University of Science and Technology (NTNU), Norway - Imperial College of London (ICL), United Kingdom - Dansk Energi (DE), Denmark - Austrian Institute of Technology (AIT), Austria - Siemens Gamesa Renewable Energy (SGRE), Denmark - Tajfun HiL (THiL), Serbia Partner organizations - Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia - DEPSYS (DEP), Switzerland - Equinor Energy (EQN), Norway - Swiss Federal Institute of Technology (ETH), Switzerland - Phase to Phase (Ph2Ph), Netherland - Instituto de Engenharia de Sistemas e Computadores - Investigação e Desenvolvimento (INESC), Portugal - NARI Technology (NARI), China - University of New South Wales (UNSW), Australia - Siemens, Denmark - Ørsted Wind Power (Ørsted), Denmark Open ESR position ESR4: Large scale data management The sheer quantum of data being created and collected across jurisdictions requires a carefully planned and proactive approach to data management. The need for fusion and integration of multiple data sources characterized by fragmented data ownership is driving innovative approaches to large scale distributed data management and integration to avoid inconsistent and inaccurate data. The aim is to investigate, design and implement a fully decentralized solution to provide efficient management of dynamically updated information and support for distributed queries. One or more domain specific use cases shall be identified within the context of the project, considering both the current and future needs of some of the involved partners. These nicely fit into the ESR research plan, owing to the need of surveying the user’s requirements to begin with; simultaneously, the uses cases can also be thought of as sources of advanced data management challenges. · Host organisation: University of Salento, Italy · PhD-enrolment: University of Salento · Duration: 36 months · Expected start date: ~Nov 2021 · Secondment: DE (4 months), TUD (4 months) · Research directors: Prof. Massimo Cafaro massimo.cafaro(a)unisalento.it Prof. Italo Epicoco italo.epicoco(a)unisalento.it Simon Tindemans S.H.Tindemans(a)tudelft.nl HOW TO APPLY: https://www1.unisalento.it/bandi-concorsi/-/bandi/view/65641043 The tender is available as “Phd call - Engineering of complex systems - 37° cycle" https://www1.unisalento.it/c/document_library/get_file?p_l_id=63872469&fold… Applicants will find the position searching the document for Research Area No. 3 N. 1 position funded on InnoCyPES research program Large scale data management and integration In particular, applicants are strongly advised to check in the same document the "Additional note for the position funded on the InnoCyPES research program”, in which all of the requirements for this position are listed. The deadline for applications is July 8 01.00 PM Italian time. - ************************************************************************************ Massimo Cafaro, Ph.D. Associate Professor of Parallel Algorithms and Data Mining Dept. of Engineering for Innovation University of Salento, Lecce, Italy Via per Monteroni 73100 Lecce, Italy Voice/Fax +39 0832 297371 Web http://sara.unisalento.it/~cafaro Web https://www.unisalento.it/people/massimo.cafaro E-mail massimo.cafaro(a)unisalento.it E-mail cafaro(a)ieee.org E-mail cafaro(a)acm.org CMCC Foundation Euro-Mediterranean Center on Climate Change Via Augusto Imperatore, 16 - 73100 Lecce massimo.cafaro(a)cmcc.it ************************************************************************************ --

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Postdoc Research Fellow position in autonomous cyber-physical systems security at ADSC Singapore
by Tan Rui (Assoc Prof) 06 Jul '21

06 Jul '21

Postdoc Research Fellow position in autonomous cyber-physical systems security at ADSC Singapore A Research Fellow position is immediately available at Advanced Digital Sciences Center (ADSC) to conduct research and development for a new project in autonomous cyber-physical systems. The project aims at studying both internal and external attacks in autonomous cyber-physical systems using learning-based approaches. The successful candidate will work on designing the attack strategy for the adversary and defence strategy for the system operator using the machine learning or deep learning techniques. The specific task will include problem formulation, machine learning or deep learning algorithm designing and testing. Qualification requirements: - Phd in computer science or electrical engineering. - Experience in machine learning or deep learning. Skills requirements: - Familiar with Python, or C/C++ programming - Experience in cyber security or cyber-physical system is a plus - Capability of independent research - Good communication skills, and work under stress How to apply: Interested candidates can apply at https://my.engr.illinois.edu/apply To receive prompt review, please also send a copy of CV to lou.xin(a)adsc-create.edu.sg. Shortlisted candidates will be notified. Illinois At Singapore Pte. Ltd./ Advanced Digital Sciences Center (ADSC) is a university-related organization affiliated with the University of Illinois at Urbana-Champaign (UIUC) established 2009 for the conduct of research in Singapore with founding funding from National Research Foundation (NRF). ADSC operates in Singapore under the Singapore-chartered Illinois at Singapore Pte. Ltd. in partnership with NRF and interfaces with UIUC in the USA for many of its support functions. ADSC is home to approximately 50 researchers and students focusing on breakthrough innovations in information technologies supporting interactive cyber infrastructures that are expected to have a major impact in transforming humans’ use of information in data-intensive, technologically developed societies. ADSC’s research mission is carried out through projects that facilitate interactions among UIUC researchers, local researchers and their industry partners. Through this, ADSC aims to enhance Singapore’s position as a hub for leading edge research. For more information about this area at ADSC, please visit ADSC's website: http://adsc.illinois.edu/ ________________________________ CONFIDENTIALITY: This email is intended solely for the person(s) named and may be confidential and/or privileged. If you are not the intended recipient, please delete it, notify us and do not copy, use, or disclose its contents. Towards a sustainable earth: Print only when necessary. Thank you.

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