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using tools such as LabVIEW, Python or MATLAB. Pre-employment checks and declarations Your employment is conditional upon the successful completion of all pre-employment or background checks required
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analysis. - Adapt the team's existing data analysis protocols as needed. Expertise in coding (Python, ImageJ) would be a plus. - Be able to communicate research results, whether within the team
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of the following areas will be beneficial. Experience with machine learning or data-driven modelling, particularly for chemical or process systems Experience with Python, or similar tools for data analysis and
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and Python Solid background in genomics Prior experience in DNA sequencing and cancer genetics is strongly preferred but not exclusively required as training will be available. Qualifications Education
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computing (Linux) environments, including shell scripting. Strong programming and data analysis skills (e.g., Python, Fortran, R). Demonstrated ability of scholarly output (peer-reviewed publications and
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models and/or probabilistic modelling, and excellent programming skills in Python and a modern deep learning framework (e.g., PyTorch or JAX) are required. Excellent skills in spoken and written English
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, for example using Python or comparable tools, and experience with GIS-based spatial analysis. The ability to work with heterogeneous geological, hydrogeological and monitoring datasets and to connect
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language (C++, Python, Rust, …) One high-quality first-author paper (journal or top-tier conference) You are expected to be somewhat accustomed to teaching, and to demonstrate good potential within research
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for classification or decoding of neural data - programming skills, especially Python Additional Information Benefits What can you expect from us? 232 vacation hours per year, based on a 38-hour workweek (1.0 FTE
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related field. Demonstrated knowledge of Python or another major programming language for data analysis and familiarity with machine learning approaches for data analysis. Knowledge of Machine Learning