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Computer science » Computer systems Computer science » Programming Technology » Communication technology Technology » Telecommunications technology Researcher Profile First Stage Researcher (R1) Positions PhD
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alloys for energy applications in harsh environments using additive manufacturing. This research involves integrating computational modeling, machine learning, and experimental investigations to design and
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, please visit: https://qbm.genzentrum.lmu.de/application/ Tuition fees per semester in EUR None Combined Master's degree / PhD programme No Joint degree / double degree programme No Description/content
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Subject area: Drug Discovery, Laboratory Automation, Machine Learning Overview: This 36-month PhD studentship will contribute to cutting-edge advancements in automated drug discovery through
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Functions Developing and implementing machine learning and deep learning models to analyze forestry, physiological, and ecological datasets Modeling plant growth, carbon allocation, stress response (e.g
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, water quality and meteorological datasets routinely collected by water utilities. The student will have the opportunity of using state-of-the-art machine learning methods (predictive analytics) to analyse
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data. Develop and apply machine learning models to estimate uncertainty in climate impact statements. Analyse spatial and temporal patterns and trends in climate-extreme impacts. Cross-validate
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. Experience in coding (e.g., Python/R/Matlab) and experience in behavioural experimentation, statistics, or machine learning is desirable but full training will be provided. Interviews for this studentship
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(https://www.unibas.ch/en/Research/Values-Ethics/Diversity-and-Inclusion.html ), we are committed to sustain and promote an inclusive culture, ensure equal opportunities and value diversity and respect in
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, spectropolarimetric inversion techniques, and machine-learning–based approaches, for the physical interpretation of solar images and spectral profiles. Special consideration will be given to applicants with experience