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Retrieval-Augmented Generation (RAG) for data retrieval and knowledge inference implementation of your machine learning pipeline in Python (using e.g. PyTorch) validation of your results in collaboration with
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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are expected. Knowledge in parallel programming is desirable. Prior knowledge in differential-algebraic equations, Gaussian processes or kernel based methods is a plus; programming experience in Python or C/C
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(e.g. Julia, Python, R) are a requirement Good programming skills in a low level language (e.g. C/C++, Fortran) will be considered advantageous Our offer A vibrant research community in an open, diverse
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to submit the dissertation after 3 years and 9 months of research. Desired requirements specific to this project include: experience with a range of relevant computer programming languages such as Python, R
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language (Python/Matlab/C++ etc.) Proficiency in English, both written and spoken Ability to work independently and to work as part of a team Good reasons to join: Look forward to a unique working
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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are an advantage: femtosecond laser and diagnostics, high power lasers, ultrahigh vacuum, programming skills (Labview, Python) Ability to work closely within a team: engineers, students, postdocs and scientists, and
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statistical data evaluation, creation of scientific programme codes using common software packages (MATLAB, Python, R) Simulation skills with e.g. molecular dynamics and alpha fold Knowledge
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for data analysis and experiment automation (Python preferred) Excellent English communication skills (written and verbal) Demonstrated ability to work in interdisciplinary and collaborative environments