31 computational-electromagnetic Postdoctoral positions at Technical University of Denmark
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engineering. We aim to unravel the logic of genome organisation and metabolic control—with the bold vision of building synthetic life. In this role, you will develop and apply computational methods to analyse
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collaborative effort, internally within experimental groups at DTU and externally with other leading universities. CatTheory has a strong infrastructure and computational facility. Responsibilities and
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Job Description If you are excited by the challenge of understanding extinction through cutting-edge computational approaches, this postdoc offers a unique opportunity. You will help develop a
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DTU Bioengineering aiming to design novel Carbohydrate-Active enZymes (CAZymes) de novo (from scratch). Using state-of-the-art AI-based protein design tools, the project integrates computational design
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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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or related fields. Preferably strong interest and foundation in immunology, immune cell assays, or translational research. Preferably experience with computer-guided protein engineering. Experience in human
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airborne geophysical observations, and strong competences in Arctic fieldwork logistics. The gravity research group has carried out airborne gravimetry since the 1990s and has an annual work programme to
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computational and experimental techniques. Play an active role in education and outreach in protein design, including contributions to teaching and mentoring activities. You must have a PhD in a relevant field
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the wider scientific community Formal qualifications You must hold a PhD degree in chemical engineering, computer science, software engineering, data science, or a related discipline. We offer DTU is a
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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