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of the programme is to enable the development of fault-tolerant quantum computing hardware and quantum algorithms that solve important problems in the life-sciences. The earliest start date is (expected to be) 1st
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of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD project falls under the collaboration between
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, computer science, and statistics The objective of this PhD project is to develop machine learning algorithms that perform efficiently and coherently across both classical and quantum computing platforms. The PhD
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driving our success in this exciting and quickly growing field. Where to apply Website https://cv.newton-6g.eu Requirements Research FieldComputer scienceEducation LevelMaster Degree or equivalent Research
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project’s principal investigator, Associate Professor Lars Rohwedder, an internationally recognized expert in the areas of approximation algorithms and parameterized algorithms, see https://larsrohwedder.com
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responsible business and governance is organised around various research environments. Further information is available here: https://www.cbs.dk/research/department-management-society-and-communica
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. The group works with modeling, algorithm development, and experimental validation, with an emphasis on rapid prototyping and deployment in real-world scenarios. Research activities include control of unmanned
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correction and/or mitigation. Knowledge about networking protocols and distributed algorithms. Experience in programming, e.g., in C++, Python or Matlab. Experience with quantum simulators, such as NetSquid
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The Bioprocess Science and Engineering (BSE) group at DTU Chemical Engineering is amongst other activities developing novel methods to measure the kinetics and stability of enzymes under industrial
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Job Description The Bioprocess Science and Engineering (BSE) group at DTU Chemical Engineering is amongst other activities developing novel methods to measure the kinetics and stability of enzymes