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-driven biocatalysis and accelerate bioprocess development. DC1: Machine learning-guided multiparametric optimisation of cytochrome P450 monooxygenase PhD enrolment: Technical University of Denmark DC2
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Science, Machine Learning, Finance, FinTech, Economics, or a related field. Candidates should demonstrate knowledge of Large Language Models, generative AI, and machine learning, with interest in financial
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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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aiming to pursue either PhD, MD, or combined MD/PhD programs as their next steps. The successful applicant will have advanced experience in one or more of the following areas: molecular biology, cell
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. The project focuses on developing an integrated approach that combines machine learning techniques with physics-based models to estimate the health of various system components. The aim is that fault diagnosis
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, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will pioneer
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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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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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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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. Where to apply Website https://www.academictransfer.com/en/jobs/359558/phd-in-addressing-rebound-effec… Requirements Specific Requirements A Master’s degree in Interaction Design or closely related