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would be doing: Process and analyse large-scale calcium imaging datasets from multisensory experiments, including neural responses from visual and auditory cortices recorded over multiple days Apply and
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epidemiology, causal inference, genetic epidemiology, and machine learning. As a PhD candidate in the project, you will: Actively participate in group meetings, design statistical analysis plans in collaboration
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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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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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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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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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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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, bioinformatics, and mass spectrometry data analysis. You like a challenge and you have a problem-solving mindset. You have good statistical skills and experience with analyzing metabolomic and metagenomic
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application-oriented research that unlocks the potential of data through rigorous analysis – advancing solutions in societally relevant domains. Your profile Master’s degree in Statistics, Industrial
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multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance · Flexible working hours, home