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demonstrated by both academic qualifications and a track record of peer-reviewed publications. Required Skills: Proficiency in programming languages such as C# (Unity), and Python or JavaScript (for statistical
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languages (e.g. Python) would be an asset. You should also have good interpersonal and communication skills and should be able to work in a multi-cultural environment, both independently and as part of a team
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(preferably python); has experience with methods and models to estimate techno-economic potential of renewable energy technologies; has knowledge and interest in the energy transition. Having detailed knowledge
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production, purification and biophysical analysis. Experience in structural biology (Xray and/or EM) and python scripting would be considered an advantage. A relevant publication record demonstrating your
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++ and Python programming languages. Experience in open source projects, GPU programming, distributed computing and cloud computing are considered to be strong assets. The position of Research Fellow at
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, Python, and R. The candidate should have a strong capacity to understand processes underlying pro-environmental behaviour from different perspectives, enabling them to simultaneously understand, use, and
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publications for high impact scientific journals/proceedings. Proficient in programming e.g. Python, PyTorch, or Tensorflow. Excellent knowledge of the English language (written and verbal) is required, as
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with lasers and/or spectroscopy and programming (i.e. Matlab, LabView/Python). You are a highly motivated, enthusiastic, critical, communicative, creative and team-oriented young scientist with a
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of proteomics or multi-omics datasets, preferably in cancer research. ML applications for biomarker discovery and validation, and predictive modeling. Programming (Python, R, c++ and/or MATLAB) and handling large
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applications for biomarker discovery and validation, and predictive modeling. Programming (Python, R, c++ and/or MATLAB) and handling large-scale biological datasets. Analysis and statistical evaluation of mass