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Field
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length scales Develop machine learning algorithms to support process optimization, predictive modeling, and intelligent manufacturing control Integrate simulation tools with in-situ sensor data from
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, volumetric data analysis, optimization methods, statistical modeling, or machine learning for scientific applications. Prior experience with cryo-EM software frameworks or structural biology data is considered
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We are looking for a Postdoctoral Research Associate reporting to the Principal Investigator Prof Yee-Whye Teh, they will be a member of the Oxford Computational Statistics and Machine Learning
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Computer Science, Artificial Intelligence, Data Science, Automation, Electronic Engineering, Economics, Human Resources Management, or a related field. Experience with general methods in machine learning, such as
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monitoring and modeling across various freshwater systems. Compile and critically review the current state of knowledge on N2O emissions and modeling in freshwater ecosystems. Acquire, organize, and analyze
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psychoactive substances, in seized drug products or clinical samples. The candidate will have the opportunity to work directly with experimentalists to validate predictions made by their machine-learning models
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collaboratively within an interdisciplinary research environment. Desirable experience with advanced AI or machine-learning methods beyond standard predictive modelling prior exposure to qualitative or mixed
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for the measurement and analysis of blood pressure, peripheral nerve activity, and renal function in models of hypertension and polycystic kidney disease, and perform related data analysis (generating computerized
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with expertise in the following four areas: (1) working with large-scale digital trace data; (2) building and running natural language processing and machine learning workflows; (3) experimental design
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or junior graduate students. A formal training, education, or certification in a secondary area (beyond the main PhD focus) such as additive manufacturing, advanced/hybrid manufacturing, machine learning