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research. The ideal candidate will have experience in all of the following areas: -large scale population genomics, demographic inference, and evolutionary genomics -graph-based pangenomics and structural
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topics within applied economics. Applicants should have experience with experimental methods and/or empirical analysis of observational data with an emphasis on causal inference. Experience with methods
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simulations, density functional theory (DFT), molecular simulations, or machine-learning potentials. Experience with generative AI, active learning, uncertainty quantification, Bayesian optimization
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Railway Mechanics is the core of the competence center CHARMEC whose research focuses on the mechanical interaction between components in trains and tracks. Among other things, the research provides
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. Python, Julia, C++, R); experience with sequencing (NGS) data, geometry or graph algorithms, statistical inference or machine learning; error-correcting codes or information theory; molecular modelling
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theory, network science, resilience theory, disruption modelling, mobility systems, urban analytics, computational social science, agent-based modelling, causal inference, or spatial data science
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, locate nests, etc) Equip songbirds with various types of loggers for tracking Analyse logger/transmitter data to reconstruct migration routes Preparing samples for DNA/RNA sequencing Bioinformatic analysis
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documents: degree certificate or a statement of the expected date of defense, and two references with email addresses. We will happily handle your application via our ATS (Applicant Tracking System) ReachMee
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A well-documented track record of research interests and achievements in an area strongly related to the project You are expected to be somewhat accustomed to teaching, and to demonstrate good
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on the candidate’s profile and selected research track. About the research project DRIVE PR – Data-Driven Product Realisation is a large collaborative research initiative at Chalmers University of Technology and the