13 high-performance-computing Postdoctoral positions at Technical University of Denmark in Denmark
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of the chemicals on droplet stability. You will be responsible for the following: Implementing AI imaging to analyze high-speed droplet movies. Relating the results to the HLD principle and performing its parameter
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Nordisk Foundation and led by Associate Professor Mikkel Schmidt (DTU Compute). In LightTrap , we will use AI to accelerate the discovery of new optical materials and that enhance the performance of thin
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quantum computing protocols using hybrid detection technologies. Explore the potential of 3D cluster states for fault-tolerant quantum computing. Publish research results in high-quality scientific journals
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-substrate interactions. Clone and express top candidates using high-throughput cell-free and bacterial systems. Perform structural and biophysical characterisation of designed enzymes Perform functional
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GitHub, and working with high-performance computing clusters will be viewed positively. As a formal qualification, you must hold a PhD degree (or equivalent). We offer DTU is a leading technical university
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to computational tools like RFdiffusion, ProteinMPNN, or AlphaFold. Experience with mammalian cell culture in two and/or three dimension Ability to perform biochemical and imaging methods Strong analytical skills
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, sequencing, cell cultivation). Plan, perform, and analyse yeast and immunological experiments independently, driving the project forward (e.g., cellular assays, immunoassays, flow cytometry, cell sorting
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of dynamic operation, which is essential for effective system-level integration. The technology should have a high and stable electrochemical performance. Furthermore, mechanical robustness is a challenge
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PhD students working collaboratively at the interface of physics and Earth science. This project offers a rare opportunity to engage in groundbreaking research with high impact across both academic and
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: Background in Data Science, Computer Science or related fields; Working experience in implementing AI models (not just loading pre-trained model). PyTorch framework is preferred; Experience with APIs