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scientific ideas. Previous experience with statistical analysis, programming (e.g., R or Python), machine learning, or genomic data analysis is an advantage but is not required. We welcome applicants who
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boundary layer methods (Kármán momentum integral method) • Numerical methods for partial differential equations • Iterative solvers for linear systems • Fluent programming in Python and/or C
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products and the bioeconomy in general. You are very well-versed working with data, models, statistics, simulations, and in general quantitative methods. Basic experience with programming (e.g. python
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Aalborg University | Witwatersrand Native Labour Association Dam, Mpumalanga | South Africa | about 1 month ago
engineering or a closely related field. You are expected to have experience with data analysis in a clinical context, as well as programming skills in R or Python and familiarity with command-line tools
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machine learning, preferably experience in probabilistic modeling, Bayesian machine learning, or graph representation learning. Programming skills (e.g., Python) and experience with deep learning
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closely related field. Documented experience in energy-system modelling, mathematical optimization, control, digital twins, or related areas. Strong programming and numerical modelling skills using Python
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algorithms. Proven experience with reinforcement learning algorithms and implementations. Experience in programming, e.g., in Python, PyTorch, TensorFlow, or similar. Curiosity and willingness to
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, data analysis and programming skills (e.g., R, python, matlab, etc). We seek candidates that are team players who can play active scientific and social roles in a diverse and international lab setting
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Python programming skills to implement and prototype research ideas. • A solid mathematical foundation to support the design and analysis of algorithms and systems. • Curiosity, motivation, and the
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advantage. The candidate should be comfortable with scientific programming, for example in Python and common machine-learning frameworks such as PyTorch or TensorFlow, and be motivated to combine