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a related field. Strong programming skills (R, Python) and experience with NGS data analysis. Proficiency in statistical and machine learning methods for biological data. Familiarity with high
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: Develop human-in-the-loop robotic simulator to provide in-silico trials for assistive robots. Build virtual human models based on ability data and machine learning. Optimize robot parameters to cater
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topics ranging across programming language (especially Bayesian statistical probabilistic programming), statistical machine learning, generative AI, and AI Safety. Key Responsibilities: Manage own academic
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innovative Research Fellow to advance research in ammonia e-cracking for sustainable hydrogen production. This position requires expertise in computational modeling, machine learning, materials synthesis, and
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responsiveness of applications; Diagnosing the issue and resolving it on demand. Job Requirements: PhD Degree with 5 years working experience in computer science, computer engineering, electrical engineering
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of machine learning and adaptive control algorithms is highly desirable. Good communication skills and ability to work well in a team environment. We regret to inform that only shortlisted candidates will be
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As a University of Applied Learning, SIT works closely with industry in our research pursuits. Our research staff will have the opportunity to be equipped with applied research skill sets
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one of the following: Econometric methods for causal inference; Data science and machine learning; Survey design and analysis; Qualitative analysis skills specialized in policy and geopolitics A good
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informatics approaches (e.g., machine learning, Bayesian statistics) and spatial data processing and analysis skills would be of advantage. Expertise in Stata, R, or other analytic tools. Strong communication
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(e.g., machine learning, Bayesian statistics) and spatial data processing and analysis skills would be of advantage. Expertise in Stata, R, or other analytic tools. Strong communication (oral and written