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, statistics, machine learning and deep learning. The project Motivation: Interpreting the genome means modeling the relationship between genotype and phenotype, which is the fundamental goal of biology
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LE STUDIUM LOIRE VALLEY INSTITUTE FOR ADVANCED STUDIES | Orleans, Centre | France | about 1 month ago
and machine learning projects involving heterogeneous data. S/he is expected to collaborate and exchange with the previous experts involved in the project and to produce efficient work to achieve
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for Artificial Intelligence. https://miai.univ-grenoble-alpes.fr/ Activities Develop and evaluate deep learning tools for MRI fingerprint data Write scientific articles Present results at international conferences
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of heat transfer and turbulence physics in wall-bounded flows through numerical simulations, data-driven modelling, and machine learning techniques. Key goals include optimising convective heat transfer
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-driven drug development. Mentor junior team members and provide domain expertise to our R&D team. Bridge Research & Product: Translate biopharma research questions into actionable machine learning
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | 9 days ago
program. The aim is to use Python code to identify the machine learning profile used in order to identify good and bad practices. The objective of this position is to develop a Python parser, a tool for
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of Python programming and a deep learning framework, preferably PyTorch. Solid knowledge of image processing, inverse problems, and machine learning. Significant research experience, demonstrated by quality
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Inria, the French national research institute for the digital sciences | Villeneuve la Garenne, le de France | France | about 1 month 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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of autonomous mobile machines integrating perception, reasoning, learning, action and reaction capabilities. The team's main research areas are: architectures for autonomous robots, human-robot interaction
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neural network or other machine learning method are available and should be evaluated before implementation. The simulator can then be used to study the nocivity of natural and synthetic ground motion