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of neural hydrology, where hydrological models are directly learned from data via machine learning (e.g., LSTM neural networks, [1]). Initially, these models ignored all physical background knowledge and did
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of the mechanisms that lead to defect formation in DED-LB, and improve process control measures to either prevent or mitigate the defects. The additionality of external controls over the laser-matter interactions
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are looking for candidates within the field(s) of chemistry, physics, nanochemistry, material science or similar. Applicants can have a background from solid state chemistry/physics, chemical egeneering
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22 Aug 2025 Job Information Organisation/Company IMEC Research Field Physics » Quantum mechanics Researcher Profile Recognised Researcher (R2) Established Researcher (R3) Leading Researcher (R4
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is a collaborative studentship between the University of Edinburgh and the National Physics Laboratory (https://www.npl.co.uk/ ). The position will be registered and hosted at the University
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Are you eager to advance your scientific career at the cutting-edge of quantum materials and nanotechnology? DTU Physics and DTU NanoLab offer a fully funded PhD position to develop groundbreaking
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that self-organize into functional units due to their chemical or physical properties—to address a wide range of diseases. A landmark achievement highlighting this potential is the rapid development of mRNA
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dynamics, or seismic monitoring of rainfall. Projects are tailored to align with the candidate’s background, interests, and long-term goals.Details:Applicants will apply to the JCU HDR scholarship process in
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Karlsruher Institut für Technologie (KIT) | Karlsruhe, Baden W rttemberg | Germany | about 12 hours ago
at the interface between detector physics and materials research. Your tasks will include: Develop a detector platform to integrate MMCs with existing synchrotron beamlines (such as the X-SPEC beamline at the KIT
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Development of novel processing techniques Modelling techniques that can inform the direction of experimental activity Physical, mechanical and materials characterisation techniques Data-driven approaches