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chromatin remodelling complexes, and benchmark their activities generate nucleosome positioning maps using sequencing-based readouts (e.g., MNase-seq, Fiber-seq) and perform quantitative data analysis
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(available for download on the following site ). Please complement with your CV, publication list, and recommendation letters. If confidential data exists that would strengthen the proposal, please indicate
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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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experience in accordance with the TVöD Bund. Social benefits in line with those of the public sector. The position is limited to a duration of 2 years. Please send your complete application documents through
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The Professorship of Public Policy for the Green Transition (PPGT) focuses on designing and evaluating policies for the green transition worldwide. The group uses a variety of methods from automated data analyses
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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
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(Sangeeta.Sharma(at)mbi-berlin.de or sangeeta.sharma(at)fu-berlin.de ). The application deadline is May 1st , 2026. For further information about the position, please contact Ms. Prof. Dr. Sangeeta Sharma
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that expenses that may arise in the context of an eventual job interview cannot be reimbursed. For more information, please contact Prof. Dr. Luca Gattinoni (luca.gattinoni(at)lit.eu ). We are looking
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computing resources for the proposed solutions the development of quantum algorithms for the efficient input and output of data sets as they occur in drug discovery leading contributions to technical reports
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advanced wet-lab experience in molecular biology and in reverse genetic approaches. • You are familiar with FAIR data handling and in silico data analysis. • You work precisely and reliable. YOU FIT TO US