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technologies in NLP, LLMs, and RAG. Programming skills in Python, including experience with machine learning libraries (e.g., PyTorch, Scikit-learn, Hugging Face Transformers) and development tools (e.g., Co
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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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possibly measurements. You will mainly do your programming work in a mixed programming environment, i.e. combining both high-level and low-level programming languages such as Python for the former and
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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
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programming capabilities (1-3 years minimum experience) in languages relevant to accelerated materials discovery, particularly Python Behavioural competencies Research - Communication (Level 3) Research
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) in languages relevant to accelerated materials discovery, particularly Python Behavioural competencies Research - Communication (Level 3) Research - Creative thinking (Level 3) Research - Teamwork
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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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. – knowledge of computer vision; knowledge of deep learning architectures; – Knowledge of C++, Python, Matlab; – Analog/digital circuits IC design capability; – Testing of electronic devices and systems; FPGA