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flows, or reinforcement learning-based design optimization. Strong programming skills in Python with experience in PyTorch, JAX, or equivalent deep learning frameworks. Ability to work independently
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Matlab or Python and a basic experience in the use of optical engineering software (for example Zemax OpticStudio, CodeV, RayJack-1) is required. You should have good interpersonal and communication skills
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, provided they have advanced training in methodological statistics You should have advanced programming skills in R or in other statistical software such as Python, or MATLAB. You should have a solid
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and written. Further expertise that would be valuable: Python software development; Natural Language Processing. Above all, you are a quick learner, proactive and eager to make things work. Our offer
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in Python and affinity with large geospatial datasets. Interest in interdisciplinary research at the interface of geoscience, engineering, and societal impact. Good communication skills and willingness
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and digitizing archival data, strong knowledge of causal inference methods, good command of R and Python. Knowledge of machine learning methods is an asset. Strong command of English; command of either
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relevant to molecular and/or materials discovery, such as DFT, MD, and ML–based property prediction. Basic knowledge of physical chemistry, thermodynamics, or electrochemistry. Proficiency in Python and
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involving the analysis of omics or twin datasets. Essential qualifications include: A strong computational background, with experience in one or more programming languages (e.g. R, Python, Perl, or shell
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for hands-on experimental characterization techniques and data analysis. Skills in programming (e.g., Python, MATLAB) and simulation tools. Expertise in photonic integration is not a must, but having relevant
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skills (Python) and knowledge of deep-learning frameworks (PyTorch) are expected. A certain affinity towards turning complex concepts into real-world practice is desired. The successful candidate is