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Field
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verification and Large Language Model (LLM) safety, focusing on extending state-of-the-art logic-based automated reasoning tools such as ESBMC (https://github.com/esbmc/esbmc ) to address safety and reliability
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-specific needs, but include: site evaluations or modeling, project coordination, interviews, data collection and/or analysis. Connections to professional practice and to emerging technology and ideas in
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Associação do Instituto Superior Técnico para a Investigação e Desenvolvimento _IST-ID | Portugal | 2 months ago
a Research Infrastructure? No Offer Description Applications are open for 1 Research Studentship(s), within the framework of project Exploring Robotlike RObot behavioRs in users’ Mental Models (ERROR
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, antigen presentation and trained immunity) using mouse models that enable CPT1A gain or loss of function. Furthermore, the bioenergetic profile of macrophages both in vitro and ex vivo will be assessed
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computational models generate hypotheses and, with the help of partner labs, validate them in controlled systems. The end goal is a mechanistic and clinically relevant map of how CIN shapes cancer behavior and
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patient stratification and combination therapy choices. You’ll be part of a tightly integrated team that uses computational models generate hypotheses and, with the help of partner labs, validate them in
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25th February 2026 Languages English English English The Department of Materials Science and Engineering has a vacancy for a PhD Candidate in machine learning and large language models (LLMs
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models. The candidate will be jointly supervised by Dr. Iris Groen (www.irisgroen.com ) and Prof. Cees Snoek (https://www.ceessnoek.info/ ). Want to know more about our organisation? Read more about
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SELECTION PROCEDURE FOR THE HIRING OF AN ENTRY-LEVEL PHD WITHIN THE SCOPE OF THE PROJECT "FIT-HEART – Metabolic flexibility as a critical factor for improving the outcomes of Heart Failure with Preserved
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learning, optimisation, system modelling, or related quantitative methods, as acquired through master’s level coursework and project work. Familiarity with data driven modelling approaches relevant to energy