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development of algorithms using modern machine learning libraries (mainly pytorch) and over the course of the project duration, the developed algorithms is expected to reach a medium to high TRL. The applicant
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, glassware, smallware’s, dishwashers, coffee machines etc. Proactively monitoring the state and quantity of items, overseeing pre-approved preventative and reactive maintenance, identifying shortfalls / issues
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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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integrated with steel slag to reduce carbon emissions. The intern is expected to have hands-on experience in machine learning and modelling tools and will contribute to this innovative research through data
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. Proficient in Microsoft Office Software (Microsoft Word, Excel, PowerPoint), Scientific Data Analysis and Graphing Tools and other relevant computer-based tools used in a modern research environment
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applied statistics and statistical machine learning within healthcare. The successful candidate will have the opportunity to shape the curriculum, drive impactful research, and contribute to public health
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approaches, i.e. machine learning. Experience and knowledge in sorbent-based CO2 capture. Experience of interaction with industry. Experience supervising students. Skills in writing bids for research grants
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publications, for stage in career, and evidence of contribution to the writing of these publications proportionate to opportunity. Experience with machine learning and/or machine vision applied to research in a
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, perception, serious games, simulation, AI, Machine Learning, sensors, decision-making, and to communicate this expertise to the Transition Engineering Lab colleagues, and employ the cutting edge knowledge in
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grow? We encourage our researchers to find and follow their passion. We offer fantastic opportunities for learning, development and professional growth. This project will provide hands-on insight