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, including quantitative, qualitative, and experimental approaches. Ideally, experience with Python, Stata, or R. • demonstrates proficiency in data collection, processing, and analysis, preferably using
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focus on the genetic and epigenetic molecular pathogenesis of pediatric T-cell leukemia (T-ALL). One particular emphasis will be on the multiomic wet- and dry-lab analysis of clonal and subclonal genomic
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/ Multi-Omics Data Integration Candidates with a strong background in bioinformatics, computational biology or epigenomics. Desirable experience includes single-cell and spatial omics analysis (scRNA-seq
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). On the research side (www.denkglobaldx.org), our department hosts a diverse and interdisciplinary team working across diagnostic innovation, clinical and implementation research, mathematical modelling, data
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partner from data sciences provides data management and AI based Image analysis, an internal experimental group, and an internal simulation-sciences group (You+Supervisor+support by lab
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discussions and team meetings Taking over project responsibility Collaborating closely within an interdisciplinary research team sincere interest in analysis of large scale data - we can provide guidance Your
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-organization. For more information go to: https://www.bauschlab.org Your Qualification: High motivation, curiosity, and commitment to scientific excellence Master's degree (for PhD) or PhD (for PostDoc) in stem
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PostDoc in "Sustaining the keystone: Rethinking Antarctic krill fishery management under climate ...
and fastest-growing fishery in the Southern Ocean, regulated by the CCAMLR, which aims to manage the fishery sustainably, relying on ecosystem-based approaches incorporating data on predator populations
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energy system optimization and control Engineering, Applied Mathematics or a comparable quantitative discipline Very good software development and data analysis skills Inquisitive and passionate about
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are modeled using information theory. We wish to investigate how interleaving can reduce the overhead and computational load due to coding coefficients required in classical linear random network coding