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: Master’s degree in biomedicine or biostatistics. Doctor of medicine degree with clinical practice experience. Certified training in R and Python software. Documented experience using machine learning and
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, dynamic programming , statistical signal processing, reinforcement learning, and have good programming skills in Python and MATLAB. - Ability to work independently and ability to formulate and tackle
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for candidates who have: Strong programming skills, particularly in Python Solid analytical and mathematical abilities Experience with machine learning Strong communication skills and proficiency in English The
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or more of the following programming languages/environments: Unity/Unreal, C/C++, C#, Python Basic understanding of the artificial intelligence and machine learning fields. Place of employment: Karlskrona
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modeling of magnetic materials using first-principles methods. Good knowledge of programming is required. Meritorious experience for the position is demonstrated knowledge of Git, Python, Bash and VASP. Good
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Python, Matlab, and R, and good UNIX knowledge are essential skills, as well as familiarity with biological omics data analysis techniques. Admission Regulations for Doctoral Studies at Stockholm
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structural biology. Merits are: Experience from protein production and purification and/or Python code development. Consideration will also be given to collaborative skills, drive and independence, and how
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learning, deep learning and relevant software framework (R and Python) is highly desired. Very good oral and written communication skills in English are required. Emphasis will also be given on personal
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optimization • Experience of multidisciplinary work and collaboration between academia and external partners. • Good programming skills in Python (Pytorch) etc. • Additional knowledge on waste and Near-infrared
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, engineering physics, biomedicine, or similar Documented skills in data-driven analysis (machine learning using python with TensorFlow, PyTorch, or similar) and computational statistics Specific knowledge of big