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Supervisor: Professor Florian Markowetz Course start date: 1st Oct 2026 Overview Professor Florian Markowetz wishes to recruit a student to work on the project entitled: “Development and
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) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic hardware. Both projects
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" (Supervisor: Prof Timothy O'Leary) uses principles from systems neuroscience to develop reliable, low-power spiking neural networks and learning algorithms for implementation in a new generation of neuromorphic
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developments such as novel algorithms to support logistics operations, novel automation approaches or the design and development of new digital support tools for logistics providers. Significant flexibility
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Ascl1 are important. We have undertaken a comprehensive discovery experiment to identify all the proteins that can physically interact with Ascl1, using a method we developed called RIME (Rapid
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used. AI methods for generating regulatory hypotheses between genes, hormones and physical properties will also be developed. Applicants must have/be close to obtaining a PhD or MPhil in Computational
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participants Ideally, practical skills in one of (a) programming, (b) machine learning, and/or (c) design Responsibilities Developing and conducting novel research projects individually and on teams Developing a
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will be defined, decomposed and assessed through attention to artefacts and practices across a range of sectors and disciplines. Focusing on the automotive context, the project will develop a
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strategies. Please upload the following: a full Curriculum Vitae including a list of publications a cover letter including a statement of your research, your relevant work experience and qualifications, and in
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increasing pressure to reduce its carbon footprint while ensuring long-term performance of infrastructure, particularly in environments that accelerate material degradation. This PhD aims to develop and