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AI in Science & Technology

@ai_sci_tech · channel · Tech · indexed since 2026-05-24
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AI in Science & Technology
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❇️ Inverted CERN School of Computing 2020 - ONLINE EVENT - Sept. 28 to Oct. 2 Dear All, The 13th edition of the Inverted CERN School of Computing (iCSC 2020), will take place as an online event from September 28 to October 2, 2020 (in the afternoons). An excellent programme is planned, consisting of lectures and hands-on exercises selected from a range of proposals by past CSC students, and focusing on the following domains: • Programming Paradigms and Design Patterns • Heterogeneous Programming with OpenCL • Computational Fluid Dynamics • Reconstruction and Imaging • Modern C++ features • Big Data processing with SQL Attendance is free and open to anyone. Connection details (link to the videoconferencing room) will be sent by e-mail to registered participants - therefore if you are interested, please register. You are not obliged to attend the full event - indeed you can simply attend the classes that interest you the most! Certificate of attendance will be provided to those who attend at least 80% of the lectures, and take a short evaluation test after the school end. More details, including the timetable: https://indico.cern.ch/e/iCSC-2020. Please feel free to forward this message to any of your colleagues who might be interested. Thank you! Kind regards, The CSC Team CERN School of Computing https://csc.web.cern.ch/
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AI in Science & Technology
💠 CALL FOR PAPERS ❇️ Machine Learning and the Physical Sciences Workshop at the 34th Conference on Neural Information Processing Systems (NeurIPS) December 11, 2020 NeurIPS 2020 is a Virtual-only Conference https://ml4physicalsciences.github.io/ ABOUT Machine learning methods have had great success in learning complex representations of data that enable novel modeling and data processing approaches in many scientific disciplines. Physical sciences span problems and challenges at all scales in the universe: from finding exoplanets in trillions of sky pixels, to developing solutions to the quantum many-body problem and combinatorial problems, to detecting anomalies in event streams from the Large Hadron Collider, to predicting how extreme weather events will vary with climate change. Tackling a number of associated data-intensive tasks including, but not limited to, segmentation, computer vision, sequence modeling, causal reasoning, generative modeling, and probabilistic inference are critical for furthering scientific discovery in these and many other areas. In addition to using machine learning models for scientific discovery, the ability to interpret what a model has learned is receiving an increasing amount of attention. In this targeted workshop, we aim to bring together computer scientists, mathematicians and physical scientists who are interested in applying machine learning to various outstanding physical problems including in inverse problems, approximating physical processes, understanding what a learned model represents, and connecting tools and insights from the physical sciences to the study of machine learning models. In particular, the workshop invites researchers to contribute short papers (extended abstracts) that demonstrate cutting-edge progress in the application of machine learning techniques to real-world problems in the physical sciences and/or using physical insights to understand and improve machine learning techniques. By bringing togeth
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onference registration that includes the workshop session and participate in one of the virtual poster sessions. Examples of accepted abstracts from previous years can be found here: https://ml4physicalsciences.github.io/ SUBMISSION INSTRUCTIONS Submissions should be anonymized short papers (extended abstracts) up to 4 pages in PDF format, typeset using the NeurIPS style ( https://neurips.cc/Conferences/2020/PaperInformation/StyleFiles ). The authors are required to include a short statement (one paragraph) about the potential broader impact of their work, including any ethical aspects and future societal consequences, which may be positive or negative. The broader impact statement should come after the main paper content (see the NeurIPS style files for an example). The impact statement and references do not count towards the page limit. Appendices are discouraged, and reviewers are not expected to read beyond the first 4 pages and the impact statement. A workshop-specific modified NeurIPS style file will be provided for the camera-ready versions, after the author notification date. Submission page: https://cmt3.research.microsoft.com/ML4PS2020 IMPORTANT DATES * Submission deadline: October 2, 2020 (extended from September 25, 2020), 23:59 PDT * Author notification: October 23, 2020 * Camera-ready (final) paper deadline: November 23, 2020 * Workshop: December 11, 2020 CONFIRMED SPEAKERS Estelle Inack (Perimeter Institute) Phiala Shanahan (MIT) Laura Waller (UC Berkeley) (More to be confirmed) ORGANIZERS Atilim Gunes Baydin (University of Oxford) Juan Felipe Carrasquilla (Vector Institute / University of Waterloo) Adji Bousso Dieng (Columbia University) Karthik Kashinath (NERSC, Lawrence Berkeley National Lab) Gilles Louppe (University of Liège) Brian Nord (Fermilab) Michela Paganini (Facebook AI Research) Savannah Thais (Princeton University) STEERING COMMITTEE Anima Anandkumar (California Institute of Technology / NVIDIA) Kyle Cranmer (New York Univers
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AI in Science & Technology
☯️ آگهی استخدام ⬅️ شرح موقعیت شغلی شرکت دانش بنیان پویا فناوران کوثر (pfkvision.com) با چهارده سال سابقه فعال در حیطه هوش مصنوعی و پردازش تصویر و متن برای تکمیل تیم تحلیل داده خود از کارشناسان نرم افزار با تجربه دارای شرایط زیر برای همکاری دعوت به عمل می آورد: ✅ برنامه نویس مسلط به Python ✅ آشنایی با NoSQL , Linux , Distributed System , Microservice ✅ آشنایی با ابزارهایی مثل: Kafka, Hadoop, Spark, Docker فرد متقاضی باید شرایط عمومی زیر را داشته باشد: 💠 دارای کارت پایان خدمت 💠 حداقل یکسال سابقه کار 💠 برنامه میان مدت برای کار در ایران 💠 روحیه کار جمعی ، پیگیری ، سرچ و یادگیری ، روحیه انجام پروژه و داکیومنت سازی 🔴 لطفا افراد متقاضی رزومه خود را به آدرس ایمیل [email protected] بفرستند.
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☯️ آگهی استخدام ⬅️ شرح موقعیت شغلی شرکت دانش بنیان پویا فناوران کوثر (pfkvision.com) با چهارده سال سابقه فعال در حیطه هوش مصنوعی و پردازش تصویر و متن به منظور تکمیل تیم نرم افزاری خود از کارشناسان نرم افزار با تجربه دارای شرایط زیر برای همکاری دعوت به عمل می آورد: ✅ Full Stack developer ✅ مسلط به برنامه نویسی JavaScript و نیز Html , CSS ✅ React native for mobile and web application ✅ آشنایی با یکی از تکنولوژهای Backend مانند: 🔹Node.js, .Net core, Django 🔹در صورت بکارگیری Django آشنایی با پایتون و در صورت بکارگیری .Net core آشنایی با C# الزامیست فرد متقاضی باید شرایط عمومی زیر را داشته باشد: 💠 دارای کارت پایان خدمت 💠 حداقل یکسال سابقه کار 💠 برنامه میان مدت برای کار در ایران 💠 روحیه کار جمعی ، پیگیری ، سرچ و یادگیری ، روحیه انجام پروژه و داکیومنت سازی 🔴 لطفا افراد متقاضی رزومه خود را به آدرس ایمیل [email protected] بفرستند
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AI in Science & Technology
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❇️ 2 ML PhD Positions at Uni Hamburg Dear Colleagues, we currently have two open PhD positions for machine learning in HEP in my group: - Statistics of Generative Machine Learning Models in Physics [1], application deadline December 1st 2020 (!!) - Fast Machine Learning for Online Triggers [2], application deadline December 14th 2020 Please consider applying or alerting potential candidates to these positions. [1] https://www.dashh.org/application/phd_topics/generative_machine_learning_models/index_eng.html [2] https://www.uni-hamburg.de/uhh/stellenangebote/wissenschaftliches-personal/exzellenzcluster-quantum-universe-qu1/14-12-20-492-en.pdf Thank you & Best regards, Gregor
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Dear All, I wanted to draw your attention to this PhD position to work on the “Development of Machine Learning Based Algorithms for Event Reconstruction of a novel Detector Technology” For more information please see https://inspirehep.net/jobs/1830275 or contact Thorsten Lux in CC. Seasonal greetings, Tobias
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