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molecular subtypes of CRC, and assess expression profiles via flow cytometry Perform in vitro studies using mouse- and patient-derived organoid models, as well as in vivo experiments employing state
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insurance and social benefits. Your profile You are a highly qualified and motivated student who would like to tackle fundamental questions in plant biology using experimental and/or computational approaches
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approaches Encouragement to pursue own research ideas Opportunity to develop an independent scientific profile Possibility to acquire funding to support future projects REQUIREMENTS: Highly motivated and
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on the candidate's profile, the tasks may be adjusted accordingly Requirements: excellent recent university degree in mathematics (Master or Diploma) with a strong background in (not necessarily all) the following
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area “Illuminating Gene Functions in the Human Gut Microbiome” that combines microbiome researchers across Germany Your profile: We are looking for a highly motivated PhD student (m/f/d) with a
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, data analysis and interpretation of the results Organization of logistical aspects of the service schedule Your profile: PhD in life sciences, preferably cell biology, plant cell biology, microbiology
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isolate and functionally characterize natural product biosynthetic gene clusters via a combination of bioinformatic tools, genetic engineering and chemical analyses. Candidate’s profile: Master’s degree in
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. 3 months): definition of common model interfaces Astos Solutions GmbH (ASTOS, Stuttgart, Germany, ca. 3 months): coupling with trajectory profiles Requirements: university degree (MSc or equivalent
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EU MSCA doctoral (PhD) position in Materials Engineering with focus on computational optimization of
properties (hardness, yield and tensile strength) and corrosion profile (rate and localization). This work focuses on machine learning-assisted PSPR optimization of recently developed lean Mg-0.1 Ca alloy
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cancer cell types Integrate multi-omics datasets (DSB maps, replication timing/direction, transcription orientation, and R-loop profiles) to identify cancer-type-specific vulnerabilities Generate