22 python-"https:"-"BCAM-The-Basque-Center-for-Applied-Mathematics" positions in Italy
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- Istituto Italiano di Tecnologia
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, machine learning and computer vision techniques, statistical data analysis, and Python programming. Activities will include field calibration and validation of models and data integration into a decision
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, visit: https://sites.google.com/view/tommaso-giovannini The ideal PhD candidate has: a solid background in theoretical/computational condensed-matter physics or chemistry (MSc in Physics, Chemistry
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related to development environments such as Python and PyTorch, as well as existing libraries for predictive maintenance. The research will also extend to digital vision systems that may be used to broaden
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field (obtained within the last 3 years). Technical Expertise: Solid experience in processing Optical and SAR imagery and geospatial analysis. Programming: Proficiency in Python for EO data science (e.g
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technical requirements working knowledge of at least one programming language (C, C++, NodeJS, Python); good knowledge of versioning tools (i.e. Git), Linux environment and programming Preferential technical
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benefits from the collaboration with several universities and research centres worldwide, most often with the closer universities of Genova and Verona. AIGO is part of ELLIS (https://ellis.eu
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(Python or C/C++) with experience in systems engineering and software development. Solid knowledge of both basic and modern methods in machine learning, NLP and computer vision, including supervised and
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of intelligent systems Solid programming skills (Python, C/C++, or similar). Experience with autonomous systems (UAVs, robots, self-driving systems) is a major plus. Ability to work independently and
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techniques with target publications in conferences such CAV, TACAS, FM, and RV; Software development of FM Unit’s tools (https://fm.fbk.eu/category/tools.html ); Participation in research and development
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Research Infrastructure? No Offer Description The requested figure will be responsible for developing and implementing both machine-learning methods for analysing images and audio files in Python, as