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machine learning tools and working on Linux High-Performance Computing platforms would be highly desirable. This is a highly collaborative role and you will work with scientists and clinicians from other
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projects. It is essential that you hold a PhD/DPhil in a quantitative or computer science related subject (e.g. Statistics, Machine Learning, Biostatistics, AI, Engineering), and have post-qualification
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Experience in analysing drugs and metabolites from human breastmilk Competency in using computer software to collect and process data, e.g. use of Excel, statistical software and machine learning approaches
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Research Associate to work on an industry-focused supply chain modelling and analytics project. The post-holder will have expertise in optimisation modeling, machine learning techniques, excellent
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team working with epidemiologists, parasitologists, mathematicians, machine learning scientists, laboratory technicians, field assistants, health practitioners/policymakers, and global health ethicists
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of influential knowledge leadership bringing the School together with students, business and society in learning to make a difference. Over the last five years ULMS has engaged in extensive recruitment of academic
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optimisation modeling, machine learning techniques, excellent programming skills, and a strong track record of developing both academic and publicly facing research outputs. This role is based
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Intelligence (AI) and development of Machine Learning (ML) models and Federated Learning. 11. Engage in continuing professional development activities as appropriate. 12. Undertake any other duties of equivalent
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researchers to find and follow their passion. We offer fantastic opportunities for learning, development and professional growth. This project will provide hands-on insight into, and potentially lead to, career
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and PhD students. Research spans a wide range. Current interests include: Bayesian statistics; modelling of structure, geometry, and shape; statistical machine learning; computational statistics; high