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project activities and writing reports Your Profile MSc or PhD in a relevant field Experience with Machine Learning modeling Coding experience, preferably Python Basic knowledge of databases tools and
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quantitative biomedical sciences. Experience with R and/or Python packages Experience working with Linux, including shell scripting Preferred Qualifications: PhD or MD/PhD degree in Bioinformatics, AI machine
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of Python programming and machine learning tools, deep learning, and large language models is desirable. The fellow will be based at the Engineering College of the São Paulo State University (UNESP), in its
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knowledge in at least of the following techniques : EEG, MRI, TMS • Good programming skills (python, R, matlab). • Knowledge of legal and deontological frameworks • English : B1 to B2 Know-how • Organise
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, computer science (medical image processing), medical physics. Computer skills: Python, C++ (ITK, RTK). Languages: English required, French optional. Website for additional job details https://emploi.cnrs.fr/Offres
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developers, electrical and mechanical engineers. Experience and strong understanding of machine learning algorithms, mathematical modelling, and applications of AI. Proficiency in Python, leading ML frameworks
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applications of AI. Proficiency in Python, leading ML frameworks (e.g., PyTorch, TensorFlow, JAX), and scientific libraries (e.g., NumPy, SciPy, scikit-learn) Familiarity with medical images such as x-ray, CT
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qualifications: Experience with VASP and high performance computing Proficiency in programming (Python or C or C++ or Fortran) Experience with developing machine learning interatomic potentials A solid background
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for those who can also program in Python and know standard network analysis techniques and metrics such as community detection and centralities. Prefernce for those with experience in geo-spatial analysis
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: Qualifications required: The candidate must have a PhD's degree in Biophysics, Biology, Bioengineering or equivalent. Expertise in image/data analysis and coding is required (Python, Image J). Experience in cell