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Field
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sustainability issues. In particular, the “Probability/Optimization” group focuses on the theoretical understanding of algorithms used in machine learning, for training large neural networks and tuning
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(Research Assistant) or PhD degree (Research Associate) in computer science or a related area or equivalent experience. Familiarity with standard machine learning libraries/data analysis, specifically as
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will also use focussed ion beam milling scanning electron microscopy (FIB-SEM) to prepare infected cells for in situ cryo-ET. The resulting tomographic data will be analysed by machine-learning assisted
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will hold a PhD (or close to completion) or possess equivalent research experience in a relevant computational field such as data science, artificial intelligence, machine learning, computer science
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task essential for grid stability. The goals of the project are twofold. The first goal is to accelerate the solution of the large mixed-integer optimisation problems required to balance energy. The
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Max Planck Institute for Demographic Research (MPIDR) | Rostock, Mecklenburg Vorpommern | Germany | about 4 hours ago
for Demographic Research, Rostock This network focuses on “scientifically motivated engineering” to design, build, and test digital prototypes—such as machine learning models and large language models—that serve as
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Electromagnetic simulation We also welcome the researcher from different fields: AI (machine learning, big database, etc) Semiconductors As a minimum requirement, you must have a PhD degree in Electrical and
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incremental optimization. We seek researchers to develop next-generation machine learning methods that fundamentally rethink how large-scale AI systems are trained, fine-tuned, and deployed. Our focus is on
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, creative start-ups, big data, big ambitions, hands-on learning, and a whole lot of robots, CMU doesn’t imagine the future, we invent it. If you’re passionate about joining a community that challenges the
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proteins and pathways implicated on disease pathogenesis. We are currently analyzing brain, CSF and blood, multi-omic data (transcriptomics, proteomics and metabolomics), from a large collection of well