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surface properties on their energy balance and gas exchange. Experiments will be accompanied by mathematical modelling of the physical processes involved. How will you contribute? In accordance with any
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PhD or equivalent qualification in computer science, statistics, mathematics, physics, and/or engineering, or a degree in biological science with demonstrated experience in computational and statistical
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physical sciences, engineering, advanced microscopy techniques, and DNA nanotechnology. Biochemists, synthetic biologists, bioengineers, chemical biologists, chemists, or candidates with a computational
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physics (e.g., Turing patterns). This will involve: (i) developing new analytical/theoretical tools for the study of reaction-diffusion systems, (ii) performing large scale, machine-learning-assisted
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Qualifications MINIMUM QUALIFICATIONS: PhD (or equivalent) in biology, bioengineering, computer science, physics, or a related field Strong scientific curiosity, motivation, and rigor Strong communication
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NORPOD is a collaborative postdoctoral program of the Nordic EMBL Partnership for Molecular Medicine . The partnership is a network of four national research centers across the Nordics and the
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(FSTM) at the University of Luxembourg contributes multidisciplinary expertise in the fields of Mathematics, Physics, Engineering, Computer Science, Life Sciences and Medicine. Through its dual mission
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Pneumatic Tires, Structure-Process-Properties Relationships. As part of it, we are currently looking for a postdoc on machine learning for road characterization. How will you contribute? Do you have proven
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organised into two research groups focused on 1) the realisation of sustainable polymeric and particulate materials (SPPM) and 2) the chemistry and physics of smart / responsive polymeric and particulate
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: completed scientific higher education degree (PhD) in the field(s) of Earth system science, physics, climate physics, geosciences, mathematics, computer science or a comparable field demonstrated experience