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candidates who are interested in joining our team as PhD fellow. The position is available from October 1, 2025, or as soon as possible thereafter. The Ravnskjaer lab is headed by Assoc. Prof. Kim Ravnskjaer
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, e.g., in C++, Python or Matlab. As well as experience with running programs on quantum simulators and quantum computers. - Familiarity with the basic concepts of error correction codes. - Knowledge
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in working with large data sets and the development of numerical models. Basic knowledge of glaciology or geodesy. Good expertise in programming, e.g. in Python, MATLAB, or other high-level programming
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. Neil Sinclair and Prof. Marko Lončar), where TFLN devices will be fabricated at DTU and TFLT at Harvard. Scientific Environment The project is funded by The Novo Nordisk Foundation and anchored at DTU
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optimisation, hands-on experience from modelling membranes with CFD software tools such as ANSYS Fluent, and proficiency in programming languages such as Python, MATLAB, or similar. You must contribute
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thermochemical TES. Your main supervisor will be Prof Adriano Sciacovelli and you will join the Thermal Energy Section at DTU Construct. Your work will contribute to a paradigm shift in how complex TES systems
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operators, transformers/LLM) and NN training. Strong Python programming skills (as a plus: C++ or Julia) and knowledge of scientific computing libraries (numpy, scipy, JAX…) and machine learning libraries
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. You will work under the supervision of Prof. Francisco C. Pereira, Assoc. Prof. Carlos Lima Azevedo (DTU), Dr. Biagio Ciuffo and Dr. Georgios Fontaras (JRC). You will work on research focused
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and robotics). Proficiency in Python, MATLAB, and/or C++ programming dialects (knowledge in other languages will be valued). Marine fieldwork experience with deployed platforms is an advantage. You must
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academia and industry. You will be involved in the “DTU Alliance” project in collaboration with Prof. Anna Scaglione at Cornell University, with the opportunity to undertake a research stay of 5–9 months