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focuses on understanding brain tumor biology and developing innovative diagnostic tools to improve patient care. These efforts are enabled by our department’s world-leading collection of brain tumour
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, academic, and industry partners to advance functional precision medicine in Acute Myeloid Leukemia (AML). Funded through the MWK BEGIN program, our group plays a central role in building the computational
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-dimensional cell cultures are important to enable realistic cell environments for disease modeling and to analyze cell interactions. This position will address the question of how one can develop minimally
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, and/or human rights. Your responsibilities: You will develop and carry out your independent research project You will contribute to teaching in sociology (teaching load is 4 hours per week during
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Limitation:Temporary (2 years) Contract:TV-L Your tasks Develop and implement computational pipelines for processing and analyzing ONT RNA/cDNA sequencing data. Apply machine learning and signal processing approaches
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interdisciplinary and international team of computational and experimental scientists, gaining unique opportunities to develop novel computational tools and pipelines for the analysis and integration of genomic
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sensor data, with applications in disease modeling and the development of material science-based innovations. These efforts aim to optimize system performance and uncover novel biological insights in close
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to supervise PhD, Master and Dr. med (thesis as part of medical studies in Germany) students. The fellow will also have the opportunity to teach as part of the institute’s Masters and doctoral program but will
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to teach as part of the institute’s Masters and doctoral program but will not be required or expected to do so. The salary is paid according to the German TV-L system (the salary agreement for public service
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Contract:TV-L Your tasks The available research projects aim to understand and develop strategies to treat heart disease You will combine epigenetic, chromatin interaction analysis and single-cell approaches