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- Delft University of Technology (TU Delft)
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diffusion models Familiarity with CT imaging workflows or radiological image-analysis pipelines Ability to develop reproducible research code in Python, preferably using PyTorch Experience with explainable AI
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for early drug discovery Basic coding skills (e.g., Python, KNIME, or similar) A strong publication record in peer-reviewed journals Scientific curiosity, creativity, and a goal-oriented research mindset
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several—of the following: policy analysis, survey research, quantitative analysis, scientometrics, stakeholder co-creation. Advanced proficiency in R and python for statistical and corpus analysis Ability
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quantitative skills (e.g. advanced statistics, programming in Python, R, or Matlab). You have experience with neuroimaging and/or computational modelling of cognition and behaviour (e.g. reinforcement learning
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Expertise: Deep experience in Large Eddy Simulation (LES) and a solid understanding of Atmospheric Boundary Layer (ABL) physics. Programming: Strong proficiency in C++, Fortran, or Python, and experience
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. You are motivated to conduct applied research in close collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python
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collaboration with industry partners and SMEs. You have a track record of scientific publications in relevant venues. You are proficient in Python and relevant machine learning frameworks such as PyTorch
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programming in Matlab and/or Python. You are hands-on in lab work and skilled in experimental design. You bring creativity, an assertive attitude, and perseverance. TU Delft Delft University of Technology is
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). Understanding of or interest in regulatory environments, sustainability, or policy modeling in supply chains. Solid programming or modeling skills in tools such as Python. Strong analytical, writing, and
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communicate in academia. Excellent computational skills (e.g., R,Python or comparable). Fluency in written and spoken English (at least C1 level). The capacity to participate in an interdisciplinary