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context (i.e., different data source from human to technical, from knowledge to generative AI models). Collaborate with software engineers to integrate the management infrastructure within the Digital Twin
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. This will include implementing and applying software analysis pipelines and interpreting disease-related data together with experimental and clinical collaborators. Bioinformatics analyses guided by prior
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metal bearing mudstones and carbonates Core logging and sample selection Place results in a 3D context e.g. using modelling software such as Leapfrog Develop a paragenesis from all stage of diagenesis
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Postdoc "Interferometric SAR Data Processing and Analysis for Implementation in the 3D-ABC Founda...
efficiently the processing results between processing facilities for FM training to the AI and HPC teams in the 3D-ABC consortium Develop the required software data management and processing interfaces Analyse
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the foundations for reliable decision support and Monitoring, Reporting, and Verification (MRV) systems for reducing greenhouse gas emissions in Danish agriculture, particularly exploring conditions for the uptake
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Postdoc in Psychiatric Epidemiology: Linking Register and Trial Data to Study Postpartum Depressi...
registers. Familiarity with survey-based data collection and handling of longitudinal data. Skills in quantitative analysis using relevant statistical software (e.g., STATA, R, or SAS). Experience with
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microscopy. Integrate analysis pipelines with imaging hardware workflows, contributing to software automation for tile stitching, autofocus, and multichannel detection. Validate models and workflows using
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advanced statistical analysis Expertise in youth research is an asset Proficiency in data processing and analysis software (e.g. R, Stata, Python, SPSS) Proficient in at least two of the following languages
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candidate will have a strong background in bioinformatics, statistics, and computational biology, with demonstrated expertise in statistical and bioinformatics software. The ability to thrive in a
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Bioinformatics with at least one first-author publication, accepted or submitted Experience with machine learning will be a plus (e.g., Tensorflow/Keras/PyTorch). Experience with software containers and/or