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field) and ground-based (radio) data - Use of various software codes: (i) radio emission simulation code, (ii) solar wind propagation code. - Development of software (preferably in Python) for data
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, longitudinal modelling, machine learning and multivariate approaches. Proficiency in programming (e.g., MATLAB, Python, or R), handling large datasets, and working with complex analysis 2 pipelines is an
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learning, computing, data science, biomedical engineering, or a related field at the level of a master degree Programming skills (Python) and experience with common machine learning platforms Experience with
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skills. experience in data analysis, quantitative modeling and programming (e.g., R, python); knowledge of nutrient and/or agrochemical cycles in agriculture; excellent scientific writing skills in English
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. Desirable qualifications Documented Experience with Python and/or another scientific programming language. Documented Experience with image processing, computer vision or machine learning or Documented
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perception, optimization, or control will be an advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch
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data science, biomedical engineering, technical medicine, or a related field. You should have strong programming skills (Python, PyTorch), deep learning knowledge (multimodal learning, longitudinal
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implications for both fundamental and medical sciences. Job requirements MSc degree (or nearing completion) in physics, biophysics, computational biology, or a related field. Strong programming skills (Python
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work; Experience with data analysis, such as statistics, data management, etc.; Experience in scripting/programming (e.g., R, Bash, Python); Strong interest in understanding human impacts on ecological
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, Python, Matlab, or C++ A keen interest in advancing our understanding of marine ecosystems, polar regions, and/or biogeochemistry Proficient communication skills in spoken and written English Experience in