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that can be tested directly against large-scale viral genomic data. The central challenge of this project is to connect microscopic evolutionary mechanisms—mutation, selection, and ecological feedback
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, electrochemical impedance spectroscopy) and analytical techniques (SEM-EDX, XRD, Raman). You have a drive towards understanding the underlying mechanisms behind the observations and like to think in terms of e.g
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hold an MSc in Earth science, environmental science, data science, physics, mathematics or computer science, with practical machine learning/artificial intelligence courses and relevant project and
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applicants should have a strong academic record with a solid background in Machine Learning. Knowledge of Vision-Language-Action models and Novel View Synthesis techniques is a strong plus. Good programming
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and you’re not fazed or overwhelmed by the ambitious nature of the project. You also have: An MSc degree in Civil Engineering, or a related field. A solid background and keen interest in NDT
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of these systems, holistic system‑level design automation is the logical and necessary next step. Achieving this requires moving beyond domain‑specific solutions by integrating mechanical, electrical, software, data
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who has made a ground-breaking contribution to virology research. The prizewinner receives a monetary award of EUR 35,000. Submit nominations:Is opening 12 August 2026 Regulations M.W. Beijerinck
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Master’s degree in Biomedical Sciences, Medical Biology, or a related field. Affinity with pathology, immunology and metabolism and a strong interest in understanding disease mechanisms. Strong wet‑lab
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26 Jan 2026 Job Information Organisation/Company University of Twente (UT) Research Field Engineering » Materials engineering Engineering » Mechanical engineering Researcher Profile First Stage
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this? Scientifically driven and meticulous – You are motivated to dissect molecular mechanisms underlying cardiac disease and translate them into meaningful insights. Strong academic foundation – You hold a Master’s