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Field
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knowledge about how cells function by peering into their molecular components in time and space, from single molecules to native tissue environments. Your studies in Bioinformatics will be in the project
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the Biochemistry, especially Bioinformatics, program the applicant must have passed courses within the first and second cycles of at least 90 credits in either, a) Chemistry/Molecular Biology/Biotechnology, or b
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) biological knowledge about GRNs from bioinformatics and system biology, (b) graph theory and topological data analysis for network modeling from mathematics, and (c) robust machine learning (ML) and GenAI from
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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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: 11.07.2025 Limitation:Temporary (2 Jahre, Verlängerung angestrebt) Contract:TV-L Your tasks Single-cell multiomics in primary cells: wet-lab experiments and performing bioinformatic analyzes on the single-cell
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clinical management. We are seeking a non-clinical PhD candidate with high-level bioinformatics skills to join our internationally renowned, multi-disciplinary team in Newcastle. This position provides
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Research Assistant/Associate Professor (Proteomics and Bioinformatics), Non-Tenure Track - (220000I3) POSITION SUMMARY Location: On-site at the University of Maryland School of Pharmacy, Baltimore
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the analysis of the complex data and cellular models (Big Data and Kavli Institutes). The DPhil will provide the student with multidisciplinary skills including specialized training in bioinformatics, genetic
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xenograft (PDX) models. To this end, the candidate will have direct access to cutting-edge mass spectrometry and advanced bioinformatics infrastructure. The project is part of the collaborative research
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cross-disciplinary in nature, building skills in molecular biology, bioinformatics, ecological mathematical modelling, algal physiology and cultivation. We are looking for a highly self-motivated