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Field
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Oncology Department at City of Hope is the largest Radiation Oncology enterprise in the southern California with more than 25 Linear Accelerators (Linacs) including special designed machines such as MR
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a PhD in machine learning, math, stats, physics, or some other technical area by the time the position starts. Additional Qualifications Candidates should have significant experience in some area of
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econometrics and machine learning, is highly desirable. You are well-organised and capable of managing multiple tasks to meet deadlines, with excellent written and verbal communication skills for producing clear
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development of transparent, closed-loop control system for individualized diuretic closing including the validation and advancement of machine-learning and control algorithms, building production-oriented
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experience – 40% Evaluation of academic performance and/or relevant professional experience in machine learning, AI, software engineering, or security-related domains. Research track record and scientific
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Responsibilities: Electrochemical process on interface phenomena Battery testing under different conditions Simulation of scaled up process. Interface with machine learning group on data base set up Battery safety
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an air force base involving UAV activities Visit to a navy base Battlefield walk ("staff ride" learning experience) Visit to the security fence and a checkpoint to learn operations/procedures Visit
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multimodal data, enabling early detection and personalised interventions in clinical neuroscience. The candidate will take the lead on machine learning and computational analyses, primarily supporting our
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design and discovery, including the use of artificial intelligence (AI) and machine learning (ML) techniques. The hired candidate will focus on computational aspects of immune repertoire analyses
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, machine learning and AI, statistical computing, big data and AI applications and prediction in biology, medicine and infectious diseases. Potential research projects include (but are not limited