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environmental impacts of digital activities. You will lead projects modelling the energy usage of different computing equipment (personal computers, servers, High-Performance Computing infrastructure
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learning tools to recommend reaction conditions for the synthesis of novel TRPA1 inhibitors. The project “A machine learning approach to computer assisted drug design” is led by Docent Juri Timonen
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with a background in cognitive psychology, data science or computer science and a willingness to develop skills in computational models of cognitive processes, statistical methods, and programming (R
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- and post-operative management and assessment of animals after transplant (micro)surgical procedures. Experience with mouse models of survival surgery is necessary. For appropriately qualified candidates
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Senior Researcher in Synthetic Biology and Metabolic Engineering of power-to-X utilizing Microorg...
. Responsibilities and qualifications Your overall focus will be to establish and lead a strong research program in the field of synthetic biology and metabolic engineering of non-model microorganisms, with the aim
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engineering, and hyperparameter tuning to produce resilient and high-performing models. · PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field Strong track record
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@umoncton.ca]Context & Motivation:Because of their extreme computational needs where workloads demand rapid and significant shifts in power consumption, next-generation high-performance computing (HPC
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the design of innovative analytical and computational techniques to analyze,integrate and model multi modal data for the onset and progression of AMD. In doing so,the successful postdoctoral fellow will
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in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ You will be hosted in the Process Modelling, Automation and
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Computer-adaptive methods and multi-stage testing Application of machine learning in psychometrics Predictive modeling of educational data Methodological challenges in cohort comparisons Advanced meta