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Entry requirements Essential Educated with an undergraduate honours’ degree (or equivalent qualification) in Computer Science/Engineering or in a relevant subject area. Significant experience in graphic
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We are looking for a motivated and curious PhD student with a background in computational biology, bioinformatics, or genomics to join our research team. This exciting project, funded by
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System-on-Chip (SOC) Technologies provide an opportunity to underpin a number of capabilities for AI and related capabilities on platforms. This research, within the context of automotive systems, explores opportunities to design a high-performance RISC-V-based platform to support analytics and...
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Computer Science PhD Scholarships PhD scholarships are available in the Computer Science CDT, with some attached to specific projects. Eligibility: Home and international fee paying students
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, and Internet-of-Things / Industry 4.0 technologies. Knowledge of computer science principles and modern AI approaches in computer vision and/or time series analysis is a plus. The position requires
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. International applicants may require an ATAS (Academic Technology Approval Scheme ) clearance certificate prior to obtaining their visa and to study on this programme. How To Apply You must apply through
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A PhD opportunity at the EPSRC Centre for Doctoral Training in Quantum Information Science and Technologies at the University of Sussex School of Mathematical & Physical Sciences The University
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to the fields of synthetic biology, bio-derived materials, and bioinspired design. The outcomes of this research will provide a foundation for understanding and replicating natural mineralisation processes
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Engineering, Physics or Materials Science Excellent English written and spoken communication skills The following skills are also highly desirable: Ability to program in Matlab, Python or similar Strong
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as Aeronautic and Aerospace Engineering, Biomedical Engineering, Product Design and Engineering (a minimum honours degree at UK first or upper second-class level). Experience in computational modelling