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alongside longstanding regional partner organizations in Kenya. Qualifications: Expertise in a relevant discipline (e.g., epidemiology, ecology, nutrition, economics) with PhD conferred by the start of
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field. Experience: At least three years of strong record of research productivity in machine learning and artificial intelligence. Expertise in AI/ML and interests in business and policy applications
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PhD candidate in the automated detection of measurable residual disease in hematological malignancie
(deep learning, probabilistic modelling, generative AI) or machine learning Proficient in Python or R programming Strong communication skills in English Strong interpersonal skills Ability to work
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validating deep learning models for the prediction of disease progression from ophthalmic data. Skills include working with image or computer vision-based toolkits, development of multimodal, multidata type
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the broader community. You have BS in machine learning, cybersecurity, statistics, or related discipline with eight (8) years of experience; OR MS in the same fields with five (5) years of experience; OR PhD in
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the broader community. You have BS in machine learning, cybersecurity, statistics, or related discipline with ten (10) years of experience; OR MS in the same fields with eight (8) years of experience; OR PhD in
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in the same fields with five (5) years of experience, OR PhD in the same fields with two (2) years of experien. Willingness to occasionally travel to customer sites, conferences, and offsite meetings
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modeling, multilevel (random effects) modeling, and analysis of data from complex samples Experience with management and analysis of big data Experience with machine learning and related approaches (e.g
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control under high inverter-based resources (IBRs). • Develop and apply artificial intelligence (AI)/machine learning (ML) techniques for power system planning, operation, control, and cybersecurity
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immunology through innovative spatial analysis of the tumor microenvironment. Requirements Successful candidates will have a PhD, MD, or equivalent degree in immunology, cancer biology, pathology, or a related