12 high-performance-quantum-computing-"https:" Postgraduate positions at Forschungszentrum Jülich
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scientific advisors and opportunity to mentor students Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats): https://www.hds-lee.de/about/ A
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graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Further development of your personal strengths, e.g., via a comprehensive
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Bayesian computational statistics, differentiable programming, and high-performance computing, the project aims to deliver robust, interpretable, and scalable methods for metabolic flux analysis. You will
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information about our institute here: https://www.fz-juelich.de/en/ias/ias-8 Your Job: Develop physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic
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the comprehensive training programme of the graduate school HDS-LEE https://www.hds-lee.de/ A structured doctoral degree programme via our doctoral researchers’ platform JuDocs https://www.fz-juelich.de/judocs
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Your Job: We are looking for a PhD student to develop learning-based surrogate models for predicting stress fields in patient-specific arteries. Especially high stresses in plaque can lead to
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of results through high-quality publications and open-source software contributions Your Profile: Master’s degree in chemical engineering, biotechnology, computational biophysics, bioinformatics, data science
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, energy systems, or material sciences A Masters degree with a strong academic background in mathematics, computer science, physics, material science, earth science, life science, engineering, or a related
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Your Job: This PhD project aims at relating precisely timed spike constellations across subsets of neurons to low-dimensional manifolds of high-dimensional space of population neuronal firing rates
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surrogates or approximators, such as random forests or shallow neural networks, trained to mimic the outputs of the original computations at a fraction of the cost. This hybridization aims not only