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About the role: We are seeking two researchers to join our team to work across four EU-funded projects, led by Professor Evina Katsou. The StreamSTEP project focuses on optimizing resource-efficient
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research systems are configured in the most optimal and user-friendly way and that any associated training and communications will be delivered in a clear, concise and timely manner. You verify and authorise
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• Uncertainty quantification around LLMs • Constrained optimal experimental design (active learning) • Combining models and combining data / Realistic simulation of clinical trials • Developing
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to watch this introductory video . What will you be doing? You will play a key role in enhancing data quality and optimizing our business systems and processes. You’ll collaborate across teams
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sensing, and Electromyography (EMG) tools to understand user-device interaction and optimize real-world rehabilitation performance. The student will gain experience in AI, human biomechanics, smart textiles
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modelling tools (CST or HFSS) - Fabricate and test for optimal electromagnetic performance, such as bandwidth, return loss, insertion loss and power-handling. - Develop and characterize new bonding/alignment
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optimizing cloud solutions that support business objectives of the JOINER project. The ideal candidate will have hands-on experience with AWS and VMware, deep knowledge of hybrid clouds including the network
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medical imaging). Examples include Bayesian optimization for molecular or materials design; machine learning for single cell data; physics-based ML for turbine design and astrostatistics. These posts
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Manager and Estates to ensure the facility environment is maintained to an optimal state, as well as working with the Faculty Safety Manager, to ensure that health and safety policies, systems and
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to define project workflows. You will manage project scope, timelines, and communication, ensuring clear information flow among team members and stakeholders. As Well as maintaining and optimizing JIRA board