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The applicant must: hold a PhD in a relevant field (e.g. computer science, artificial intelligence, machine learning, computer vision, animal science, biology, veterinary medicine, or a related discipline) have
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. The position bridges machine learning and molecular science, with opportunities for collaboration, mentorship, and impactful research. About us The Department of Computer Science and Engineering (CSE
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Description of the workplace The Division of Secure and Networked Systems at the Department of Electrical and Information Technology conducts broad research in cryptography, computer security
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) training personalized computational models in new contexts, and (iii) studying in-silico clinical intervention strategies. The postdoctoral fellow will have the opportunity to: Learn about computational
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testing and collaboration with infrastructure owners or managers - Experience in supervision - Knowledge of data-driven methods, signal processing, or machine learning - Familiarity with sustainable
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–classical algorithms or optimization methods Background in uncertainty quantification, reduced-order modeling, or machine learning Experience collaborating in interdisciplinary research teams A doctoral
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network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce using UPSC transformation and somatic embryogenesis pipelines; evaluating drought
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, and demonstrated ability to develop computational pipelines for biological datasets. Experience in statistical modeling and/or machine learning applied to biological systems, with the ability to link
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loop/TAD structures. - Perform comparative analyses versus Populus tremula; apply network modelling and machine learning for regulatory inference. - Functional validation of candidate TE‑CREs in spruce
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at the intersection between analytical chemistry, chemometrics and life sciences. As a postdoc in this project you will learn to use and help to develop cutting-edge methodologies linked to vibrational spectroscopy and