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analysis, focused on selected electrodes or brain regions. We would like to investigate how graph deep learning models can be designed to capture dynamics in brain signals for the accurate detection, and how
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treatment, material and energy flow analysis, integrated data modelling, systems dynamics modelling, circular economy, sustainability assessment performance, decision-support tool design Month when Interviews
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Max Planck Institute for Multidisciplinary Sciences, Göttingen | Gottingen, Niedersachsen | Germany | about 2 months ago
PMID33762348 , PMID30224749 and PMID32743075 . Requirements M.Sc. degree in molecular-, cell-, structural biology, computer science, digital image analysis or related fields that included minimum six months
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also contributing to public engagement and the collaborative life of the project. Academic Research Conduct socio-legal and policy analysis with key stakeholders in the selected country. Carry out
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. The candidate will be embedded in the Explanatory Data Analysis group at the Leiden Institute of Advanced Computer Science. The group develops algorithms and theory that enable domain experts to describe data
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, PMID30224749 and PMID32743075 . Requirements M.Sc. degree in molecular-, cell-, structural biology, computer science, digital image analysis or related fields that included minimum six months long
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psychology) or data analysis (e.g., data science, statistics) Affinity with data science (e.g., complex statistics, machine learning or computational modelling) or willingness to develop relevant skills (in
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experience with spatial data analysis using GIS tools or spatial libraries and familiarity with common land-use datasets would be advantageous familiarity with environmental or agricultural economics research
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-solving skills preferably skills in next generation sequencing-based methods and bioinformatics/computational data analysis Benefits: international working environment with communication in English 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