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State programme promoting young researchers (Tenure-Track Programme). The professorship is affiliated with the department of Medical Systems Biology (https://www.med.uni-wuerzburg.de/en/systemimmunologie
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the Reinhart-Koselleck programme for innovative high risk-high gain research. Requirements: university degree in chemistry or physics and profound knowledge in computational and theoretical physics/chemistry
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-regulatory network changes. The project is part of the HEROES-AYA consortium of the German Decade against Cancer, a collaboration between multiple sites in Germany, and the Computational Biology lab of Anna
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sequencing, RNA sequencing, mouse models, iPSC-derived organoids, and functional genomics approaches. The lab has strong collaboration partner in computational biology and bioinformatics, and the candidate
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computer science, bioinformatics or related fields Solid understanding of machine and deep learning and relevant frameworks (e.g. Pytorch or Tensorflow, Keras, scikit-learn, OpenCV) Proficiency in Python, Linux and
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(independently and in our team) involvement in teaching across different life science study programs at the Faculty of Medicine Required skills: Ph.D. (or comparable) in Bioinformatics, Computational Biology
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* Contribute to the supervision of PhD students and junior researchers Your Profile: * PhD in Bioinformatics, Computational Biology, Systems Biology, Biostatistics, or a related field – (Doctoral degree should
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prostate tumor samples. This position requires a strong background in both experimental proteomics and computational data science (R and Python), with an emphasis on LC-MS/MS workflows and long-term cohort
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PhD Student / Postdoctoral Researcher (gn*) Molecular Biology Reference Number: 10836 Fixed term of 3 years | Full- or Part-Time (65% or 100%) | Salary Grade TV-L E13 | Centre of Reproductive
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, epigenetics, cardiovascular science, computational biology, or a related field A strong background in chromatin biology, gene regulation, and/ or cardiovascular biology Prior experience with genomics