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assays, complemented by mass-spectrometry-driven chemical profiling and machine-learning-supported multivariate analysis. Where relevant, CRISPR-Cas-based genetic perturbations in mammalian cell models
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perform 3D single-particle tracking and establish pipelines to characterise the particle motion using a combination of established tracking algorithms and machine-learning-based approaches. Additionally
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» Biomedical engineering Medical sciences » Other Researcher Profile First Stage Researcher (R1) Positions PhD Positions Application Deadline 30 Mar 2026 - 23:59 (Europe/Stockholm) Country Sweden Type
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%). You will work at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model
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at the intersection of numerical analysis, uncertainty quantification, and scientific machine learning. The research will primarily focus on probabilistic methods for data-driven model reduction, with
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highly interdisciplinary setting combining microbial mutagenesis assays, mammalian cancer models, next-generation sequencing, bioinformatics, and machine learning. Experimental data will be integrated with
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information about us, please visit: www.dbb.su.se . Project description The candidate will develop machine learning (ML) strategies, primarily revolving around interpretable ML and generative AI, to study
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Postdoctoral Fellow in Evolutionary Systems Biology The Department of Zoology is one of the departments within the Faculty of Science and has approximately 80 employees including researchers, PhD
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Foundations. 360 000 SEK each year and is taxfree. Qualifications We seek a driven and motivated bioinformatician to contribute to our research program Eligibility: A PhD (or foreign degree deemed equivalent
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motivated bioinformatician to contribute to our research program Eligibility: A PhD (or foreign degree deemed equivalent) in bioinformatics, epidemiology, statistics, or a closely related field, awarded