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. · Proficiency in programming languages such as Python, Pytorch/JAX, AWS. · Knowledge of energy market mechanisms and policy considerations is a plus. · Excellent communication skills and the ability
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and/or Python. Experience in, and aptitude for, complex statistical modelling (inc. mixed effects regression models and/or Bayesian statistics). Excellent written and spoken English. Desirable (traits
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analytical skills have a strong programming background with experience in using Python, C/C++, and/or Java, etc. strong interpersonal skills with demonstrated ability to communicate (written and oral in
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of neutron-induced nuclear recoil backgrounds with multiple scatters in LZ. Measurement and simulation of muon-induced background in the LZ experiment. You will work alongside Prof Davide Costanzo and Prof Dan
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is to address these challenges by developing innovative integrated chassis controllers and processes that seamlessly coordinate multiple actuators from the outset. The research will explore advanced AI
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is to address these challenges by developing innovative integrated chassis controllers and processes that seamlessly coordinate multiple actuators from the outset. The research will explore model-based
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specific interest in dynamics and effects over time. Such questions are not limited to one charitable cause, but can also involve the interplay between multiple charitable causes. In this project, you will
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”, led by Associate Professor Valeria Vitelli. Successful candidates will work on Bayesian models for unsupervised learning when multiple data sources are available, mostly tailored to the case
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measurements to the results of existing techniques using backscatter to quantify forest attributes through synthetic aperture radar imaging. The overall project, spanning multiple institutions, aims to produce a
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. PV field system data analysis (time-series data analysis with JMP software and /or Python). Accelerated ageing procedures (IEC standards). PV module failure modes. Corrosion. Strong communications