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Field
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, algorithms, data pipelines, and research software prototypes contribute to optimisation, simulation, sampling, or uncertainty-modelling approaches for complex systems analyse infrastructure, spatial, temporal
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Systems At the Institute of Climate and Energy Research – Energy Systems Engineering (ICE-1), our focus is on developing models and algorithms for simulating and optimising decentralised, integrated energy
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(Automated Design of Algorithms) group in the machine learning clusters at LIACS, Leiden University, and supervised by Jan van Rijn and Holger Hoos. You will be working intensely with other project members
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constraints. The postdoc will work at the interface of reinforcement learning and computational epidemiology, focusing on the development of new reinforcement learning algorithms. The project will consider
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develop algorithms for this purpose. The group collaborates with several national and international research groups, edits one of the major journals on data privacy (Transactions on Data Privacy), and has
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Max Planck Institute of Molecular Cell Biology and Genetics, Dresden | Dresden, Sachsen | Germany | 3 months ago
conferences, contribute to publications, and support a positive and collegial team culture. Essential qualifications Doctoral degree (PhD) in Molecular Biology, Biochemistry, Cell Biology or a related life
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 2 months ago
/en/offres/2026-10301 Requirements Skills/Qualifications Compétences techniques et niveau requis :We are seeking a motivated PhD candidate with a strong background in one or more the following areas
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that amplify human potential. The successful candidate will engage in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems
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in innovative research projects in ML, focusing on developing novel ML algorithms, enhancing human-AI collaboration, and exploring systems tailored to dynamic, human-centered environments. They may
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algorithms at scale on ORNL's computational resources, including the Frontier supercomputer, addressing critical challenges in science and engineering. Communicate and coordinate experimental results with