155 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "Simons Foundation" positions at Technical University of Denmark
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motivated to move the area of enzyme engineering to the next level, while having a positive impact on our world. When joining our team, you get the opportunity to use the latest algorithms in machine learning
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regarding the positions, please contact Rajmund Mokso (rajmo@dtu.dk). You can read more about the department https://physics.dtu.dk and the 3D imaging center https://3dim.dtu.dk . If you are applying
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Job Description A fully funded 3-year PhD position is available at DTU Aqua, within the newly established project NOW-LUMP, funded by seabreak (https://www.aqua.dtu.dk/nyheder/stenbiderprojektet?id
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department project that develops lifelong learning opportunities in digitalisation for wind energy. In this role, you will take the lead in defining and executing communications and marketing priorities
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likely use ICP-MS to measure catalyst degradation in the electrolyte after testing. The potential to teach, advise Bachelor/Master student thesis projects, or be involved in proposal writing is also
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) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric eNzyme and bioproCess dEsign), and it will focus on: Expression, characterization and application of enzymes from University of Turin and other
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include: Supporting the delivery of the 3D-CIRCULAR master and doctorate programmes, including coordination of hybrid (online/in-person) teaching and supervision activities. Updating and refining learning
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Villalobos) and Consortium partners (https://cordis.europa.eu/project/id/101227645 ). Our focus is to guide innovation at an early stage by assessing the benefits (society, economic and environmental
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you are our new colleague. In EE&SB you will Have the opportunity to shape your project within our frame Teach and supervise younger scientists Go to international conferences to promote your work Be an
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mechanics, vibrations, and their active control, as well as machine elements and design optimization. The section has a scientific staff of about 25 people and 20 PhD students. The research rests