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the role Overview of the role We are seeking a highly motivated Research Fellow in Machine Learning to join the PharosAI team, focusing on developing novel machine learning methods in computer vision
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Supervised Machine Learning and Reinforcement Learning. The objective is to significantly enhance battery performance and longevity. While conventional methods rely on either physics-based models or high-level
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develop computational statistical methods to estimate the prevalence of modern slavery. We will then use these methods with partners in the law enforcement and third sectors to understand how modern slavery
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at home. The number is even higher for older people and those who were treated for more serious illnesses/injury. The overall aim of the research study is to identify and estimate the “hidden costs
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this emerging research programme Applicants should be familiar with methods for estimating comparative effectiveness using RWD, e.g., NICE’s TSD 17 , NICE’s RWE framework . You will be encouraged to develop your
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capturing real human mental performance, constrained by limited time and subject to systematic errors, requires transforming rational models into process models that approximate probabilistic calculations in
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epilepticus. You will work in the group of academic neurologist and computer scientist Dr Gregory Scott, with a team of collaborators having expertise in translational neuroscience, clinical neurology, signal
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, development needs, and interest. An estimated 20–25% of the population is affected by inflammatory skin diseases, the most common of which include eczema, psoriasis and acne. Easing the burden of these diseases
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capability Fluency in relevant models, techniques or methods and ability to contribute to developing new ones High level of competence in computer programming, with C++ an advantage. Ability to communicate