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Institute National De La Santé Et De La Recherche Médicale | Paris 15, le de France | France | 4 days ago
equivalent in systems biology, computational biology, bioinformatics, or a similar field. The candidate should have good programming skills in Python or MATLAB, and ideally R. Good knowledge of biochemistry
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strong background in statistics. Experience with human EEG and gut microbiota, as well as programming skills (Python, Matlab), are advantageous. Very good English language skills are required. The ability
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, Neuroscience, or a related field. Candidates should have strong skills in statistics. Programming skills (e.g., Python) and experience with PET or MRI imaging and data analysis are desirable. Furthermore
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equivalent) in Psychology, Neuroscience, or a related field. Candidates should have strong skills in statistics. Programming skills (e.g., Python) and experience with PET or MRI imaging and data analysis
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programming skills, preferably in Python, with experience in deep learning algorithms Experience with Raman and/or FTIR imaging is a plus High motivation to work with optics and their biomedical applications
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. Candidates must have proven ability to work with large datasets, coding with Python/Fortran/C++ and ideally experience with high-performance computing. Applicants from an industry background are encouraged
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, Psychology, or a related field, to be awarded before March 1st, 2026. Essential skills include an ability to code (e.g., Python, R) and interpret data, knowledge of machine learning and statistics, and a
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competence in programming with Python and working on Linux based platform is essential for this position. Further, we are looking for a doctoral candidate who meets the following requirements: A background and
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highly desirable, alongside knowledge of MATLAB/Simulink/Python or similar tools. Familiarity with sustainability frameworks (e.g., ESG, Mission Life-cycle Assessment) and interest in interdisciplinary
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on the topic (2,4). Training and Development Training will maximise future employability in academia and industry: Programming and geospatial data analysis using Python/R. Machine/deep learning techniques