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Field
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modelling Disseminate research at conferences and workshops Selection Criteria Experience with LCA, ideally prospective LCA Programming skills, preferably python Knowledge or interest about environmental
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programming skills (in Python, R or similar) and experience with large-scale data analysis using bioinformatic tools and pipelines to analyse and interpret biological data Attributes and Behaviour • Be
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, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language skills, ability
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strain engineering is a plus. Data analysis skills (e.g. in Python, MATLAB or similar) are a plus. Excellent communication skills in English, both written and spoken Strong motivation to work
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, Cheminformatics, Computational Biophysics, or a closely related field Strong programming skills (e.g., Python, C/C++) Knowledge of machine learning frameworks (e.g., PyTorch, TensorFlow) Very good English language
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) physics, geosciences, meteorology, oceanography, or similar. You have strong programming skills (Python or similar). You have affinity with spatiotemporal data analyses, remote sensing and numerical
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data. You bring first experience with biostatistics methods, e.g. with mixed-models. You are familiar with data analysis using programming languages like R, and/or Python. You have excellent
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system modeling is beneficial but not mandatory First programming skills, ideally in Python Independent and analytical way of working Reliable and conscientious working style Fluent written and spoken
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experience with algorithms relevant to computational biology documented programming skills, e.g. in Python and R very good communication and organizational skills with the ability to work to timelines, both
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qualifications A masters degree in neuroscience, physics, evolution and ecology, or related quantitative fields. Prior experience with Python or Matlab, and a willingness to learn analysis tools. Excited about