153 machine-learning-"https:" "https:" "https:" "https:" "https:" "https:" "University of Waterloo" positions at Chalmers University of Technology in Sweden
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an innovative spirit, in close collaboration with wider society. Chalmers was founded in 1829 and has the same motto today as it did then: Avancez – forward. Where to apply Website https://academicpositions.com
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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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complex behavior under demanding operating conditions presents a significant modeling challenge. This project addresses that challenge by combining machine learning with constitutive modeling, while
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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
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the start. The position is a fixed-term appointment of four years, with the possibility to teach up to 20%, which extends the position up to five years. A starting salary of 34,550 SEK per month (valid from
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to teach on the undergraduate/master’s level. The position is meritorious for future roles in academia, industry, or the public sector. Contract terms Full-time temporary employment for a maximum of two (2
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data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. The applicant is expected to develop and apply data-driven and machine learning-based methods
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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