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the charging schedule (V1G) to consume energy at optimal times. Another form incorporates equipment that allows the vehicle to discharge energy back into the household or the grid (V2X). This project aims
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Optimization-based control explores the use of optimization algorithms for feedback control of dynamical systems. For example, model predictive control (MPC) is a widely used optimization-based control method
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algorithms that would allow the delay and/or suppression of hysteresis effects in dynamic stall through the use of control surfaces, for example, allowing the safe recovery of aircraft from post-stall
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adapted based on the abilities and needs of patients. Moreover, automatic intelligent algorithms will be developed in to make the control intuitive, natural and adaptive. Such that the model can learn new
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attendance at events, cohort information, funding awards. Liaising with partner Universities for data where necessary. Schedule management board and committee meetings. Record and circulate accurate minutes
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Developing a clinical pathway to support nurse led whole genome sequencing for neurological diseases
on the acceptability of a nurse led WGS pathway. The interviews will be semi-structured and guided by an interview schedule. Topics will include stakeholder views on the potential benefits of nurse-led WGS, views
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Deadline: Applications accepted all year round Details The aim of this project is to develop scalable and efficient techniques and algorithms for localisation in different environments, based on data in
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. Interviews are scheduled to take place the week commencing 26th May. Should you have any questions about the role in advance of your application please email: buildzero@sheffield.ac.uk. About you We
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information extraction. Advanced algorithms will be developed to obtain useful information such as the 3D flame topology and spread velocity. The candidate should have a good background in mathematics and they
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: Facilitate comprehensive user training sessions for the relevant Ascelus platforms, both before and after ‘Go-live’ deployment for the E-IMMUNE project. Establish service support schedules to address user