622 computational-physics "https:" "https:" "https:" "https:" "INRAE" PhD positions in United Kingdom
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-of-the-art AI and computing facilities, receive tailored training and professional development, collaborate with experts across disciplines, and contribute to open-source tools that advance the wider AI
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., statistical modelling, Artificial Intelligence/Machine Learning) Experience in computational biology and bioinformatic analysis Proven ability to write detailed, technically accurate reports on complex research
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on brain cancer cells. Cancer cell microtubules have large electric dipole moments and are influenced by a process in which an electric field can affect the way in which the dipoles organize themselves in
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, Computer Science, and Business. Academic Criteria: Bachelor's (Honours) degree in Law (or a cognate subject) at 2.1 or above (or overseas equivalent), or professional experience/qualifications; and Master's degree
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Verification Tools: Develop AI algorithms that automate the verification process, ensuring systems meet required safety and performance standards. Health Monitoring Algorithms: Implement AI-based monitoring
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We are recruiting for an exciting research role as a Research Assistant/Data Coordinator, for the Children’s Surgery Outcome Reporting (CSOR) programme. This position is ideal for candidates with
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techniques from multiple fields spanning materials science, condensed matter physics, electronics and biochemistry. It includes Co-Supervisors with expertise across Graphene and 2D Material production, device
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computer science, mechanical engineering, or aerospace engineering. You should have programming experience applied to physics/engineering problems and/or experience with machine learning and ML. The University
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students from all nationalities. They support a full stipend at UKRI rates (currently £20,780 per year) and tuition fees for international/home candidates for the duration of the programme. How to Apply All
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potential to unlock critical savings in the design process. This project will allow this potential to be explored and quantified, making use of University of Manchester's existing world class high fidelity