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academic environment. About the role: The post is offered as a full-time, fixed-term contract for an initial period of one year. The successful candidate will develop and implement novel analytical pipelines
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analytical techniques, opportunities to supervise students, and involvement in manuscript preparation and future grant applications. It is essential that you hold (or are close to completion) a PhD in cell
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-learning models based on first-principles data and apply these methods across increasingly complex structures and chemical systems. The role will involve both methodological development (datasets, models
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previously been subject to various analyses. The analytical data is currently preliminary and incomplete. You will work with the unpublished dataset, identify data gaps and to carry out new analytical work
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of Immunity – Artificial Intelligence (CoI-AI) Programme, a pioneering initiative that integrates controlled human infection models, advanced immunology, and AI-driven analytics to accelerate vaccine discovery
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, explainable AI (XAI) analysis and data-flow mapping, on welfare-AI systems in the UK, Netherlands and Sweden, contributing to comparative insights and high-quality project outputs. They will collaborate across
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are looking for a researcher with a PhD (or near completion) in engineering, data science, computational social science or a related discipline, with experience in data analytics, NLP or machine learning. You
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successful in this position, you will ideally bring the following: For the Networking and AI position: Completed a PhD in Computer Science, Electrical & Computer Engineering, or a closely related field Expert
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academic excellence. Ready to be part of our team? Let’s shape the future together! Your personal sphere of play: Your future position is at the Institute of Business Decisions and Analytics in the working
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-lab role focuses on the computational analysis and methodological development of third-generation and single-cell sequencing data to understand the role of transposable elements (TEs) in early mammalian