39 programming-"https:"-"Inserm"-"FEMTO-ST" "https:" "https:" "https:" "https:" "https:" "U.S" "U.S" Postdoctoral positions at Technical University of Denmark
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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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www.kt.dtu.dk/research/dpc and https://www.kt.dtu.dk/ . If you are applying from abroad, you may find useful information on working in Denmark and at DTU at DTU – Moving to Denmark . Application procedure Your
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and hybrid detection technologies. Plan, distribute and follow up on tasks with the rest of the team. Report effectively on progress and plans. Publish research results in high-quality scientific
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Raza, sraz@dtu.dk . You can read more about our research on the Applied Nano-Optics webpage . You can read more about DTU Physics at https://physics.dtu.dk/ . If you are applying from abroad, you may
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position funded by the EPSRC project INDIMO: Invariant Discovery and Monitoring for Message-Passing Programs, starting around March 2026 (flexible start date). The successful candidate will join the Systems
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programme cohorts. Facilitating collaboration between academic staff, students, and external stakeholders to ensure smooth and effective programme delivery. Supporting dissemination, evaluation, and quality
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development, particularly in LabVIEW, C++ and Python programming for high-precision measurement systems. As a key member of our team, you will lead the development and optimization of our high-speed
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should have the following qualifications: Experience in software development, programming with Python, C++, etc. Good/strong knowledge of robot operating systems, robotic control and virtual
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characterization of soft scaffolds with programmed morphological characteristics and tailored mechanical properties. The research will be supervised by Associate Professor Stavros Gaitanaros. As part of the project
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software skills Proven experience with CFD automation, e.g. using PyFluent or similar Python APIs for meshing, solver control, post-processing and data management. Solid experience programming in Python