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, machine learning, mathematical modelling, or a related field, to join our research team in the Department of Applied Health Sciences. The successful candidate will work on an NIHR funded methodology project
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-transportation system, we are looking for a: PhD Student in Data-Driven Policy Optimization for Transportation and Energy (100%) Project background Our energy and transportation systems are rapidly transforming in
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Understanding (Prof. Dr. Martin Weigert) Research areas: Machine Learning, Computer Vision, Image Analysis Tasks: fundamental or applied research in at least one of the following areas: machine learning
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. The student will perform ‘big data’ analysis of patient cohorts including time-based evaluation of the impact of introducing CT-FFR as a national health intervention into a healthcare system. Exploratory
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computer programming in R and Python *Formal training or experience applying quantitative and spatial methods to human-environment questions *Excellent academic writing and communication skills in English
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, the candidate is expected to contribute to the development of novel workflows for joint inversion of multiple data types (e.g., borehole acoustic or seismic data) in the context of geosteering. The specific tasks
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, data analysis, or energy research (postdoctoral experience preferred for senior roles). Technical Skills: Proficiency in Python, R, or MATLAB Experience with time series forecasting, machine learning
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collaborative, impact-focused problem solver who wants to be part of a dynamic team. Information about the Shih Lab: Learn more about the innovative work led by Dr. William Shih here: https
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PhD project. In addition to electromagnetic geophysics, the candidate is expected to contribute to the development of novel workflows for joint inversion of multiple data types (e.g., borehole acoustic
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++, or Go, and frameworks like PyTorch or TensorFlow, is highly advantageous. Experience in developing and deploying machine learning models, particularly in natural language processing (NLP) and large