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Field
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. The teaching workload is expected not to exceed 30%. Selection Criteria Scientific background and knowledge Educational experience Scientific computing/machine learning skills Strength of the provided research
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or experience in nontraditional research publication methods and collaborative notetaking software (e.g., Roam Research, Obsidian, Notion). ? Familiarity with cloud computing and machine learning techniques
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Researcher (R3) Country Morocco Application Deadline 1 Oct 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
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: Appropriate PhD in related field Knowledge, Skills, and Abilities: Familiarity with appropriate laboratory and technical equipment; ability to effectively use a computer and applicable software to create data
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research on the topic outlined above is paramount Candidates are expected to be interested in working at the boundaries of several research domains PhD degree in computational biology, bioinformatics
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completed Ph.D. within the last 5 years in Computational Biology, Bioinformatics, Machine Learning, Artificial Intelligence, Virology, or a related field Strong programming skills in Python, R, or Julia, with
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simulations of PDEs, deep learning, neural networks. Our research interest: Our focus is on theoretical and computational biological physics, ranging from the study of molecules to cells. We strive to leverage
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, government agencies, and/or private sector entities to stimulate innovation, capacity-building, and sustainability of research and scholarly activity at KSU. This position is part of an NIH-supported program
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environments. Collaborating closely with AI researchers to integrate quantum-derived features into peptide design pipelines. Participating in regular group meetings, preparing technical reports and manuscripts
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an opportunity to address these challenges using powerful computational approaches. By combining unique transcriptomic and proteomic data with novel strategies in machine learning and systems biology, we aim