35 parallel-processing-bioinformatics "https:" positions at Utrecht University in Netherlands
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external link , you will play a central role in advancing the group's research through the development and application of state-of-the-art bioinformatics workflows for antigen identification
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-Independent Acquisition (DIA), Parallel Reaction Monitoring (PRM), Quantitative proteomics workflows, Data normalization and quality control strategies, Strong experience in processing and interpreting
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design, train and implement ARCA: an AI foundation model for crop microbiomes. You will work at the interface of deep learning, bioinformatics and microbial ecology, using large-scale microbiome and
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computer simulations of coastal dynamics in a parallel PhD project conducted at WUR and provide context for visualisations of historic landscapes developed by a postdoc at NIOZ in a collaboration with
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, phenotyping, bioinformatics and predictive modelling. The project gives you the opportunity to work across scales: from thousands of plants and complex microbiome datasets to mechanistic experiments with
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external link . An inspiring and highly interactive scientific environment covering various disciplines ranging from Developmental Biology, Cell Biology, Neurobiology, Biophysics, Bioinformatics and
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other genome-editing technologies, Agrobacterium-mediated transformation, bioinformatics, plant phenotyping or microscopy, DNA methylation analysis (e.g. bisulfite sequencing), or plant tissue culture
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Lab AI ( Floris Bex and Jelte Mense ) and the Natural Language Processing Group ( Albert Gatt ) at Utrecht University. Together, we want to explore how small models can extract useful information on
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research, both within the field of Clinical Psychology. Your academic profile aligns with the mission and vision of the Clinical Psychology department (https://www.uu.nl/en/organisation/clinical-psychology
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responsibilities include: Designing the research project focusing on topics related to global talent interdependencies and innovation; Collecting, processing and analysing large-scale data (e.g