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of the GRISLI model Code programming in Python and Fortran Write scientific articles - good level of English required Analysis of a large set of GRISLI simulations and sensitivity study Presentation of results
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Université Grenoble Alpes, laboratoire TIMC, équipe GMCAO | Grenoble, Rhone Alpes | France | 33 minutes ago
Requirements Specific Requirements This project will require a candidate with experience in: Image registration algorithms (non-rigid is a plus) Advanced Python programming skills (especially with Torch / Keras
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Processing Skills required: - Medical computer programming: python, 3D slicer, LCmodel (optional), FSL, spm, ants) - Artificial Intelligence skills and deep learning experience - Proficiency in Tensorflow
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BioEngineering Experience with fluidics devices, 3D printed devices, 3D cell culture models and bioinformatics/computational biology (e.g., R, Python) is an asset Team player Proficient knowledge in English is
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required (e.g., Python, Mathematica, Matlab). Some knowledge of nonequilibrium statistical mechanics (Boltzmann and Vlasov equations) and magnetism (spin dynamics, Landau-Lifshitz-Gilbert equation) is
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- Ability and interest in conducting experiments in a controlled environment (tank experiments) - Knowledge of Matlab or Python required - Knowledge of numerical simulation software such as Comsol
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, training, evaluation) Proficiency in C/C++ and/or Python for systems and AI development Ability to design and run experimental evaluations on real systems Excellent scientific writing and communication
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must have skills in sequence data analysis using bioinformatics (e.g., using Python, R or any suited programing language). These skills must be attested by the contribution to at least one publication in
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contribute to the development of a proof of concept obtained at University Côte d’Azur for accessing the content of a metabolomics knowledge graph (KG) with a large language model. It is Python prototype of a
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learning or applied mathematics. Required skills and qualities: - Fluency with Python programming for data analysis or machine learning, - Knowledge of statistical or probabilistic modelling techniques