17 machine-learning "https:" "https:" "https:" "https:" "https:" research jobs at Chalmers University of Technology in Sweden
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and automated floor-plan recognition, to fill data gaps and harmonise information from disparate sources. Learn more and watch our project video here: https://sb.chalmers.se/digital-material-inventories
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Are you interested in developing machine learning algorithms that provably help us make better decisions? Join us as a post-doc in the Division of Data Science and AI, Department of Computer Science
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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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Join and help us to derive global forest biomass data from the European Space Agency’s Biomass satellite mission. If you have interests in remote sensing, machine learning and forests, this is the
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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
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link
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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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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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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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projects in data-driven nutrition, such as: statistical modelling, AI, and machine learning on large epidemiological cohorts, diet and health data analysis of omics data (metabolomics, proteomics, microbiome