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the doctoral programme in question, the following are also required: Good knowledge in mathematics, statistical thermodynamics, and scientific programming (using, for example, Python, Fortran, C/C++) Excellent
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Machine Learning Integration Develop and implement machine learning algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC
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. change detection, semantic segmentation, or multimodal fusion, experience in deep learning for image analysis using time series satellite data, excellent programming skills (Python, PyTorch/TensorFlow
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in mouse models and cell cultures. Analyze and interpret omics data using bioinformatic pipelines in Python and R. Perform experiments in cell culture and animal models to validate the findings
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fluid dynamics and vascular modeling in microenvironments Skills in data analysis and image processing (e.g., Python, R, ImageJ) Ability to mentor junior researchers and contribute to team leadership What
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for the processing of medical images. Fluency in Python programming language. Familiarity with Bash. Excellent communications skills in English, both verbal and written. We are looking for someone who is motivated
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algorithms to enhance the design optimization process Create predictive models using Python-based frameworks (e.g. scikit-learn, PyMC) to accelerate design iterations Integrate ML approaches with finite
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development. Qualifications Requirements for the position are: M.Sc. in engineering, neuroscience, statistics, quantitative biology, physics, mathematics or a related discipline. Fluency in Python programming
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related field. At least three years of documented professional experience in bioinformatics-related system development. Excellent knowledge of Python or similar programming languages. Experience using Git
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development) of different simulation tools, mainly the GEANT4-based ldmx-sw framework (https://github.com/LDMX-Software/ldmx-sw ), written in C++, maintained on github and configured via python. You will work