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» AlgorithmsYears of Research ExperienceNone Additional Information Eligibility criteria - PhD in one of the following areas (or related fields): * Machine learning / deep learning * Quantum computing / quantum
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. • Strong knowledge of signal processing methods and machine learning. • Familiarity with regulatory and ethical constraints in research involving sensitive data. • Ability to work closely with
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statistics and/or machine learning Specific knowledge • Proficiency in scientific computing • Knowledge of machine learning packages in Python or R • Proficiency in English (minimum level B2), as the postdoc
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perception for robotics; machine learning. o An interest for approaches based on foundation models. o Proficiency in open-source libraries: Pytorch or equivalent, OpenCV, Open3D, PCL, etc. o Programming
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relevant to the project's theme and activities. Solid experience in molecular simulation and/or machine learning is required, along with a good knowledge of associated theoretical tools (experience in
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 3 days ago
, CIRAD AMAP, CIRAD PHIM, CIRAD PBVMT, INRAE ePhytia, INRAE IGEPP, INRAE LISAH, IRD EGCE, IRD IEES, Univ. Paris Saclay, TelaBotanica). This is a postdoctoral position in Machine Learning, more
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skills (one or more of the following strongly desired) Exploratory analysis of massive datasets (machine learning methods) Spatial data analysis and Geographic Information Systems (GIS) Forecasting and
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the Job related to staff position within a Research Infrastructure? No Offer Description The LIG brings together nearly 450 researchers, lecturers, PhD students and research support staff. The position
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on food craving and health-related decision-making. To this purpose, we will use a combination of brain imaging, behavioral measures, and machine-learning techniques. Activities The successful candidate
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biological signals. The project will focus mainly on developing innovative models for biomedical signals with irregular cyclicity and exploring potential machine learning applications. Position Objective