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systems using tools such as MATLAB, Python, COMSOL Multiphysics, Lumerical, or equivalent platforms. Contribute to experimental laboratory work in ultrafast and nonlinear optics. Develop and optimise
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Transformers). Analysis of existing datasets. Evaluation of the trained models on suitable datasets. What you contribute Good knowledge in the field of machine learning and training neural networks. Good Python
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. Proficient in Python, with working knowledge of bash and experience using HPC or cluster environments (e.g. SLURM). A pragmatic scientist who combines technical depth with a clear translational, goal‑oriented
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the application which project you are specifically interested in. Further details on the projects can be found here: https://www.fz-juelich.de/en/jcns/careers/fellowships/tasso-springer-fellowship-program Your
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databases (potentially using Python for scripting or CMS integration); gathering and documenting user requirements through user research and analytics; leveraging tools like Google Analytics 4, Siteimprove
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support, utilizing pharmacokinetics database PK-DB and individualized patient data (more information: https://livermetabolism.com/atlas ) Requirements: - completed scientific university degree in (bio
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. Proficiency in full-stack AI development - front-end and back-end (e.g., Python, React, Vue, Node.js, Typescript, API's, databases, Git/GitHub, CI/CD, AI Coding Assistants, Infrastructure as Code
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faculty and university research policies . You act with attention to quality, integrity, creativity, and cooperation. You have strong programming skills in Python and experience with machine learning and
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related field Great interest in energy technology, energy economics and policy issues Experience in programming with Python or a comparable programming language Experience in energy system modelling is an
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. Writing and defending your PhD thesis at Vrije Universiteit Amsterdam. Where to apply Website https://www.academictransfer.com/en/jobs/359455/phd-in-environmental-determinan… Requirements Specific