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Your Job: Energy systems engineering heavily relies on efficient numerical algorithms. In this HDS-LEE project, we will use machine learning (ML) along with data from previously solved problem
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: Design hierarchical models that explicitly capture misspecifications in metabolic models Develop differentiable and scalable inference algorithms using automatic differentiation Implement HPC-tailored
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physics-aware simulations of growing cell populations, including their spatiotemporal manipulation in microfluidic environments Design and implement reinforcement learning algorithms for control and
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retreats) https://www.hds-lee.de/about/ A qualification that is highly welcome in industry 30 days of annual leave and flexible working arrangements, including partial remote work Further development of your
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retreats) https://www.hds-lee.de/about/ A qualification that is highly welcome in industry 30 days of annual leave and flexible working arrangements, including partial remote work Further development of your
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staff position within a Research Infrastructure? No Offer Description 2 Doctoral Researchers (f/m/d) in Computational and Data Science at KIT https://www.kcds.kit.edu/72.php Application deadline: January
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data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ 30 days of annual leave (depending on agreed working time arrangements) and provision for days off between
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data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ 30 days of annual leave (depending on agreed working time arrangements) and provision for days off between
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partner is possible Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in
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) conferences Unique HDS-LEE graduate school program (including data science courses, soft skill courses and annual retreats) https://www.hds-lee.de/about/ Qualification that is highly welcome in industry Further