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data (HRMS) used for non-target analysis. The projects aims to develop a combination of supervised and unsupervise machine learning stragaties for pinpointing chemicals that have high toxicity
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the complex multiscale nonlinear interactions at the origin of such extreme events. In this project, you will develop machine learning-based reduced-order models which can accurately forecast
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16 Mar 2026 Job Information Organisation/Company Université de Haute-Alsace Department IS2M Research Field Chemistry Researcher Profile First Stage Researcher (R1) Positions PhD Positions
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growth methodology based on real-time growth monitoring enabled by advanced in situ characterization tools (RHEED, ellipsometry, curvature measurements, flux monitoring), coupled with machine-learning (ML
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master’s degree with academic qualifications in digital health, data analysis, and/or machine learning applied to health research. Admission to the PhD program requires a 120 ECTS master’s degree, including
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Priorities: We seek applications across all AI domains, with emphasis on: Foundational AI : Machine Learning, Computer Vision, NLP, Robotics & Embodied Intelligence, Data Science. Interdisciplinary Frontiers
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for a/an University assistant predoctoral - PhD Position in Graph Learning 39 Faculty of Computer Science Startdate: 01.05.2026 | Working hours: 30 | Collective bargaining agreement: §48 VwGr. B1
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Essential skills, knowledge and experience: Experience with machine/deep learning development Data-Centric AI Knowledge Notions of cybersecurity and networks are optional Spoken and written English Desirable
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expression. To learn more about diversity at the U: http://diversity.umn.edu Employment Requirements Any offer of employment is contingent upon the successful completion of a background check. Our presumption
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computational models, applying statistical and machine learning methods, and integrating data across modalities to generate novel scientific insights. The Postdoctoral Fellow will lead manuscript preparation