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Field
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/antanaviciute-group-computational-biology-and-tissue-immunology We offer • World-leading infrastructure and facilities • Opportunity to learn cutting edge molecular techniques
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barriers; we are creating something new which is always exciting. The team consists of several experts who can teach you many translatable skills and knowledge from the fields of health psychology
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dedicated PhD student with a 1st class or 2:1 degree in the field of Engineering, Mathematics, Physics, Architecture or Computer Science. A MSc degree in a relevant area is desirable though not necessary
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sensitive to malicious deviations while remaining resource efficient. Solutions must operate effectively on network gateways or even capable IoT devices. The research will investigate statistical methods
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expecting to obtain, at least a 2:1 honours degree or MSc with Merit (or international equivalent) in a relevant subject. Potential PhD Project Areas Plant reproduction • Cell signalling during plant
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datasets, therefore, there will be a focus in the implementation of models for large volumes of data. The project will work in an exciting interface of statistics and machine learning and has the potential
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required, along with an eagerness to learn more detailed identification. Any specialist knowledge of ground-dwelling invertebrate taxa is a bonus. Support: The student will be based in the Ecology and
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through the following objectives: Develop a novel approach to investigate the fluid-solid coupling effect on the performance of the CMF; Using machine-learning (deep learning) methods to develop a
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participants who may require reasonable adjustments are encouraged to contact the supervisor to discuss these aspects of the project. Desirable MSc in Clinical Exercise Physiology (or other relevant discipline
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commercialisation efforts. Peer reviewed publications in medicine and psychology journals. Eligibility: Applicants should hold or expect to gain a minimum of an MSc in Psychology, Public Health, Epidemiology