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, digital twins, or related areas Excellent publication record in high-quality journals and/or conference proceedings Excellent programming skills, particularly in Python and/or C/C++; hands-on experience
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-centred AI, digital twins, or related areas 3. Excellent publication record in high-quality journals and/or conference proceedings 4. Excellent programming skills, particularly in Python and/or C
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in Environmental Modelling, Land Use modelling or another relevant field, with clear skills highly complementary to those of the JPP4JL research team Proven ability to write code in R or python
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Control engineering (experience with nonlinear systems is a plus) Machine learning and deep learning in context of physical systems Programming skills are required, with Python experience preferred. A good
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mechanical design Experience with beam shaping techniques (e.g., spatial light modulators, diffractive optical elements) Proficiency in programming languages like LabVIEW, Python, MATLAB, or C++, and
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conferences. It is essential that you hold a PhD/DPhil in computational biology, genomics, bioinformatics, computer science, statistics, or a related field together with strong programming skills in Python, R
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with R or Python tools. Experience in processing of targeted and untargeted mass spectrometry datasets Demonstrated research competence and initiative through inernational publications in peer-reviewed
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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standard imaging analysis method including use of Python (NumPy/SciPy/PyTorch/Tensorflow), Matlab, C++, version control software (e.g. git), and statistical analysis using R, SQL, etc. Familiarity with
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neurogenetics of Drosophila. This requires expertise in setting up and analysing behavioural tests, using appropriate analytical methods and software and skills in coding in e.g. R, MatLab, R, Python, as required