271 machine-learning "https:" "https:" "https:" "The University of Edinburgh" Postdoctoral positions in Sweden
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your application: A doctoral degree in automatic control, electrical engineering, computational materials science or related. Research experience in battery tests, machine learning, data-driven
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to national environmental and climate goals as well as to the Sustainable Development Goals. We are situated at Campus Ultuna in Uppsala and in Skara. Read more about the department here (https://www.slu.se/en
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multi-modal perception and machine learning. Current noninvasive agricultural monitoring systems rely primarily on passive sensing, which limits sensitivity to early-stage plant stress. This project
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of mathematics. We are not accepting applications for this job through MathJobs.Org right now. Please apply at https://lu.varbi.com/en/what:job/jobID:905918/iframeEmbedded:0/where:4 . Contact: Magnus Goffeng
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machine-learning tools. Data analyzed include precursors such as volatile organic compounds, aerosol number and mass concentrations, chemistry, biological particles, cloud and ice condensation nuclei, light
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fundamental questions about soil health in agricultural cropping systems and advance your research career in a leading international research environment. The position is part of the EU project MultiSoil (https
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, machine learning, etc. Building a quantum computer requires a multi-disciplinary effort involving experimental and theoretical physicists, electrical and microwave engineers, computer scientists, software
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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by interdisciplinary collaboration, applied research projects, and access to advanced development, simulation, and visualisation infrastructures. Where to apply Website https://www.bth.se/english
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metaproteomics approaches Analyzing large-scale multi-omics and clinical datasets to investigate individual metabolic responses to diet. The work includes applying advanced statistical and machine learning methods