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(Shannon entropy, compressibility, effective complexity and logical depth). The data basis for the analyses are two-fold: first, recent connectome data, i. e. large datasets of all synaptic connections in
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Accountabilities PhD in biochemistry, Biomedical Sciences or Chemistry. Mass spectrometry-based proteomics. Data analysis of large proteomics datasets. Experience in cell culture and molecular biology. Languages
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programming languages (e.g. R, Python) and an ability to work with large datasets Strong record of peer-reviewed publications Ability to independently design and execute experiments and interpret data Ability
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are seeking a postdoctoral researcher with experience in analysis of large datasets to examine pre- and post-diagnosis healthcare utilisation among patients with cancer in Luxembourg using insurance claims data
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of cellular aging, resilience, and fibrosis. Responsibilities Develop and implement analytical pipelines for large-scale single-cell, spatial, and multi-omics data integration Build and apply machine learning
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multi-modal models, contributing to bridge transport economics, network modelling and activity-based modelling, and leverage different types of (big) data. The applicant should be a creative and motivated
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and several notable museums. St. Louis is a vibrant, mid-sized city that offers many of the amenities of a large metropolitan area, but without the high cost of living or heavy traffic Interested
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Post Doctoral Researcher in Human-centred Large Language Models for Software Engineering, Departm...
. Required qualifications: A Ph.D. degree in Computer Science, Data Science, Software Engineering or related field. Solid research experience with using Large Language Models. Solid programming expertise in
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experience is beneficial Experience with the analysis and interpretation of large data sets, in particular high-throughput sequencing data from eukaryotic organisms Solid skills in programming and scripting
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Experience with writing scientific publications Experience in working with contaminants like PFAS, PCBs and mercury, fatty acids, stable isotopes and modelling in R A talent for working with large data sets