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in multimodal imaging. Experience in machine learning is highly valued. You will support user-driven research projects and develop integrated data workflows spanning light microscopy (confocal, super
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, and manipulation of high-dimensional imaging and mass spectrometry data Experience in designing and maintaining reproducible and scalable analysis workflows Solid foundation in statistics and machine
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data types (transcriptomics, proteomics, imaging). AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional relationships from perturbation data. FAIR
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biology, protein engineering, biochemistry. Optical engineering, fluorescence microscopy, image analysis: Development of microscopes and data analysis pipelines used to acquire and quantify high-throughput
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data types (transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function
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innovative development and application of novel data-driven methods relying on machine learning, artificial intelligence, or other computational techniques. More specifically, at NRM this research will be
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(transcriptomics, proteomics, imaging). Knowledge on AlphaFold for models in structural protein analysis/proteomics AI/ML Applications: Applying machine learning or AI to predict gene function or discover functional
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registries and biobanks. The applicant is expected to have a strong computational focus on innovative development and application of novel data-driven methods relying on machine learning, artificial
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methods relying on machine learning, artificial intelligence, or other computational techniques. Duties The position includes research, teaching and administration. Duties includes conducting research
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and/or functional imaging or application of computational modeling, machine learning and AI to understand cellular function. At least five years’ experience working within the university system, another