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materials on research topic that may be presented to small and/or large groups. Actively participates in the preparation of required technical progress reports to research sponsors. Analyzes data using
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instruments Analysing and interpreting data Writing experiment proposals, presenting results at conferences and publishing in peer-reviewed journals. Work in laboratories and large-scale facilities. Travel
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-collection costs while maintaining validity for marketing and opinion research. Design, implement, and evaluate large-language-model (LLM) pipelines for synthetic data (fine-tuning, retrieval-augmented
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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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, and contributing to a robust data infrastructure that makes large-scale, multimodal datasets FAIR and AI-ready. You will publish findings in high-impact journals, present at major international
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in core methods of machine learning/artificial intelligence. ● Experience with data warehousing and building large, curated datasets with protected health information, suitable for training large
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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. Department Specific Functions Research and Development: Develop and apply AI and machine learning models to analyze large-scale cancer datasets, including genomics, transcriptomics, and proteomics data. Data
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lead analyses of large-scale datasets, applying advanced computational and statistical methods to integrate multimodal data (including MRI, MEG, EEG, and genomic data). The postholder will work with a
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in core methods of machine learning/artificial intelligence. ● Experience with data warehousing and building large, curated datasets with protected health information, suitable for training large