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(1–4) and in related projects. We encourage potential PhD candidates to visit our webpage to learn more about the research we are conducting. The PhD candidate is expected to be enrolled in two
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/ ) at the Department of Clinical Microbiology, at Umeå University (https:// www.umu.se/en/department-of-clinical-microbiology/ ), the PhD candidate work in the Marie Skłodowska-Curie (MSCA) Doctoral Network GLYCOCALYX
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. The project will provide the student with extensive training in large-scale data integration, machine-learning methods, field-based environmental monitoring and eDNA analysis, as well as experience working
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duties as assigned. REQUIREMENTS: REQUIRED: PhD in in computer vision, machine learning, artificial intelligence, or a closely related field. Strong programming skills. Strong background in machine
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in exercise and dance interventions. Build and evaluate AI / machine learning models using labelled, collected multimodal data to classify motor and non-motor symptoms, identify digital biomarkers
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and early-onset cases without a known genetic cause. We are also interested in genetic interactions (epistasis), tandem repeats, machine learning, and other areas of AD research that have not yet been
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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publication record. Outstanding data analytics, mathematical, and computer modelling skills. Excellent interpersonal communication and oral presentation skills in English Self-driven and strong team spirit Open
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Inria, the French national research institute for the digital sciences | Montbonnot Saint Martin, Rhone Alpes | France | 26 days ago
/Qualifications Strong proficiency in at least one of these domains: astrophysics, data science (statistics, inference, and machine learning), or physical remote sensing/Earth observation. Strong skills in
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engineering (focusing on deep learning for computer vision), and the division of statistics and machine learning at the department of computer and information science (focusing on the theory behind machine