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; GIS; environmental data analysis; machine learning; numerical modelling; tracer experiments; dispersion and mixing. DESCRIPTION (topic, expectations, comments): We are seeking a researcher holding a PhD
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Funded PhD studentship in AI-assisted materials discovery at the UK National Epitaxy Facility School of Electrical and Electronic Engineering PhD Research Project Competition Funded UK Students
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Computer Engineering, along with a Master's in ECE and a PhD in Interdisciplinary Engineering. Our students are well-grounded with hands-on experience in modern engineering labs integrated with faculty
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of greenhouse gases including CO2 and CH4. The PhD project is part of the Horizon Europe Marie Sklodowska-Curie Action (MSCA) doctoral network (DN) ELEGANCE (machinE LEarning for inteGrated multi-parAmetric
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? Not funded by a EU programme Reference Number AE2025-0571 Is the Job related to staff position within a Research Infrastructure? No Offer Description Portuguese version: https://repositorio.inesctec.pt
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world. We look forward to receiving your application! Your work assignments We are looking for a PhD student to work on the development of novel spatio-temporal machine learning methods. Our world is
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of manufacturing. We have identified an opportunity to combine continuous microfluidic (µF) process models, process analytical techn ology (PAT) and machine learning (ML) to achieve a paradigm shift in bioprocess
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disease through advanced imaging and biophysical approaches. The research group hosting this position studies Contractile Injection Systems (CIS) — natural protein machines used by bacteria to deliver
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. This position is for those who plan to apply for their own grants and projects independently. Qualifications Required: PhD and/or MD of bioinformatics, computer sciences, and biostatistics. Physical Demands
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subsequent PhD in computer science, engineering, biophysics, applied mathematics, computational biology or a related field Proven programming expertise in Python (PyTorch, scientific Python) with solid