108 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" "Imperial College London" PhD positions at Nature Careers
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applicants in accordance with European and German legal regulations. Further information on data protection and the processing of personal data can be found at: https://www.isas.de/en/datenschutz . The closing
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(XRD) to characterize, at the molecular level, smectite samples from various Swedish mineral deposits. The PhD student will be part of a research group active in the area of molecular geochemistry (http
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websites. Application Process Applications for both programs must be submitted online by January 14, 2026: https://www.uni-goettingen.de/de/application/556704.html Applicants will be asked to upload a CV
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. An individual career development plan containing research and transferable courses, international research visits, mentoring and career activities, is also a central element. Please visit https://www.interact
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The Loft Group at the Functional Genomics & Metabolism Research Unit, Department of Biochemistry and Molecular Biology, University of Southern Denmark, invites applications for a PhD position focused on experimental approaches to uncover mechanisms linking adipose tissue heterogeneity to...
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& Machine Learning • Clinical pathways and decision support for patients with acute chest pain • AutoPiX – Explainable Deep Learning for Multimodal and Longitudinal Imaging Biomarkers in Arthritis • Speaking
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Declaration of interest regarding PhD project within the field of biomarker and therapeutic targe...
, or pediatric diseases (prior experience is an advantage but not required) Experience with or willingness to learn biomarker analyses (e.g. ELISA), histological techniques, and molecular assays Interest in animal
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is accessible online: https://www.tec21.fr/phd-tec21 What we offer : 7 fully funded PhD positions with employment contract, competitive salary (monthly estimate net salary between 2 050 and 2 150 EUR
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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of experience and are willing to learn new techniques. References may be contacted and interviews may be conducted to determine your potential fit within the existing team, with emphasis placed on interpersonal