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, Cascais, Riga, Vilnius, Melsungen, Ciampino, Urla and Rhodes. The PhD project will involve: The use of data analytics (statistical models, machine learning, uncertainty quantification) to monitor and
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analysis and multivariate statistics (preferably using Python), to enhance building energy performance (and/or reduce building greenhouse gas) Experience in the full spectrum of research activities including
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on the topic assigned for each position. Requirements: outstanding university degree (typically M. Sc.) in Computer Science, Data Science, Statistics, Mathematics or another relevant field study with good GPA
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multiple disciplinary approaches inclusive of SELEX technologies, bioinformatics, molecular and cell biology, molecular design, DNA nanotechnology, organic synthesis, immunology, and preclinical studies in
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require
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the development and adaptation of statistical models for analyzing the relationship between species distributions and climate Collaborate closely with other researchers, including other PhD students in connected
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analytics (statistical models, machine learning, uncertainty quantification) to monitor and predict cycling travel conditions from various perspectives (safety, crowding, travel time, comfort, etc
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mindset. You have good statistical skills and experience with analyzing metabolomic and metagenomic sequencing data. You like to work in diverse settings as you have to communicate closely with a diverse
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-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
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analyse large datasets such as the Clinical Practice Research Datalink (CPRD) and Hospital Episode Statistics to identify activity related to the treatment of community acquired pneumonia. This will require