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Pipsa Saharinen’s research group at the Translational Cancer Medicine Research Program at the Faculty of Medicine, University of Helsinki and Wihuri Research Institute invites applications
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have a PhD in Civil Engineering, Engineering Mechanics, or Mechanical Engineering. Applicants are expected to demonstrate research experience in the fields of structural modeling and machine-learning
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a final report. Active collaboration with project partners is also expected. Your profile Applicants should hold a PhD in mechanical engineering at the time of starting the position. The selected
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will join a multidisciplinary research program that combines experimental models, patient-derived materials, and advanced technologies to explore the mechanisms that preserve auditory system homeostasis
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Morocco Application Deadline 19 Sep 2025 - 00:00 (UTC) Type of Contract Other Job Status Full-time Is the job funded through the EU Research Framework Programme? Not funded by a EU programme Is the Job
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Programme? Not funded by a EU programme Is the Job related to staff position within a Research Infrastructure? No Offer Description Project and research area : The M-Carbo-Store project studies
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Postdoctoral position in structural and biophysical analysis of plant hormone transporters within...
to investigate the molecular mechanisms of plant hormone transport. The position offers the opportunity to work within an international, interdisciplinary environment, combining structural biology, biophysics, and
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to investigate the molecular mechanisms of plant hormone transport. The position offers the opportunity to work within an international, interdisciplinary environment, combining structural biology, biophysics, and
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recently completed (or be close to completing) a PhD in Computer Science, Machine Learning, Natural Language Processing (NLP), or a related field, with a thesis focused on AI, specifically LLMs
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holistic, interdisciplinary approach that bridges computational social science and computational mental health to capture fine-grained behavioral data, uncover underlying mechanisms, and design