889 evolution-"https:"-"https:"-"https:"-"https:"-"https:"-"L2CM"-"L2CM"-"L2CM" PhD positions
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Research Training Program (RTP) Fee-Offset a four-year project expense and development package of $13,000 per annum a three-month industry engagement component with Xcel Sodium a structured professional
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development, and ultimately regeneration. The key focus includes cardiac and renal tissue engineering. You will adapt techniques established in the lab, and develop new approaches, as well as new methods
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. Experience working with deep learning software stacks, extensive software development experience, and knowledge of machine learning frameworks (such as transformers, torch, Megatron, triton etc.) are pluses
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Max Planck Institute for Intelligent Systems, Tübingen, Tübingen | Bingen am Rhein, Rheinland Pfalz | Germany | 6 days ago
ongoing research efforts in the development of statistical 3D models of Horses. About us We are creating the world’s most realistic human and animal avatars for use in research, film, virtual reality
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for driving the democratisation of digital technologies, so that everyone has the opportunity to actively participate in the development, and we ensure a continued open, democratic, and inclusive society for
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funded by the Novo Nordisk Foundation and led by Assoc. Prof. Janus Juul Eriksen @ DTU Chemistry – revolves around the development of new decompositions of molecular properties into local contributions
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for gas-phase catalysis. Development and application of ultrasensitive methods to probe gas–surface interactions by means of electron spectroscopy. Operando studies of catalysts using low dose-rate and dose
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the following main activities: Design and Evaluation of e-DAC Materials and Systems. The PhD candidate will focus on the computational development of redox-active materials for electrochemical CO₂ capture
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Cluster of Excellence quantA. The group’s research combines the development of scalable photonic quantum technology for quantum computing and other quantum information applications with the investigation
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Learning with Graphs led by Prof. Nils M. Kriege. Our research focuses on the development of new methods and learning algorithms for structured data. Graphs and networks are ubiquitous in various domains