10 programming-"the"-"DAAD"-"IMPRS-ML"-"FEMTO-ST"-"UCL"-"U" "https:" Postdoctoral positions at Technical University of Denmark
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leads JWST programs and has had multiple proposals accepted from our group (GO 2420 , GO 3730 , GO 7675 ). Through international collaborations, we are also deeply involved in several other JWST programs
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. Additional information about the Exoplanet Group at DTU Space can be found at http://www.exoplanets.dk , and more details about 2ES can be found at http://www.2es.dk . Responsibilities and qualifications We
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background in thermodynamics and phase behavior of complex mixtures Excellent programming skills (e.g., Python, C++, Fortran, or similar) Experience with COSMO-based methods, including parameterization, model
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interaction and neuroscience (SINe Lab https://sinelab.org ) group, and in collaboration with Interhuman AI and Professor Line Clemmensen. The aim is to measure and understand turn-taking and bodily dynamics
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solid understanding of energy system technologies and economics is also required. Additionally, experience with other programming languages, open-source software development, project management using
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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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in glaciology, Geodesy, Earth sciences, remote sensing, or a related field. Strong skills in data analysis, programming, and handling large geospatial datasets are essential. Experience with satellite
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information may be obtained from Professor and Head of Section Wenjing (Angela) Zhang (wenz@dtu.dk ), tel.: +45 2035 2356. You can read more about DTU Sustain at https://sustain.dtu.dk/ If you are applying from
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Solid programming experience, preferably in Python Familiarity with structured data handling (e.g., SQL) and scientific workflows Documented experience with ontology development, knowledge graphs, and
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, TESPy, or similar libraries. Strong programming skills in Python or MATLAB, including use of scientific libraries (e.g., NumPy, Pandas, Matplotlib, etc). Experience with machine learning (e.g., Scikit