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Max Planck Institute for Heart and Lung Research, Bad Nauheim | Bad Nauheim, Hessen | Germany | 4 days ago
, the candidate should have extensive knowledge of DDA and DIA proteomic data processing using MaxQuant or similar software packages. Your responsibilities The successful candidate will focus on developing methods
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within the Clusters of Excellence ‘Machine Learning for Science’ and ‘Image-Guided and Functionally Instructed Tumor Therapies (iFIT)’. Requirements PhD in Bioinformatics, Computational Biology, or a
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a circular process based on users and stakeholders engagement, co-design and assessment of innovative climate services. The proposed methodology will employ high resolution regional Earth Systems
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in the consortium. Your profile PhD in the field of mass spectrometry-based proteomics Ample experience in mass spectrometry-based proteomics, including sample preparation and hands-on use of modern
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of DESPEC experiments at GSI within FAIR Phase-0Adaptation of software tools for data processing and analysisPresentation of results at international conferences and workshopsPublication of scientific
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own simulations) identification of critical biogeophysical Earth system processes and feedbacks that shape planetary resilience coordination with the other scientists in the PB-TIP project, within
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own simulations) identification of critical biogeophysical Earth system processes and feedbacks that shape planetary resilience coordination with the other scientists in the PB-TIP project, within
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Postdoc in "Navigating uncertainty: Planning marine protected areas in a changing Southern Ocean"...
productivity and strategies for sustainable management of selected marine ecosystems. Your Profile A PhD in conservation biology, geoinformatics, spatial ecology, or a related field A strong background in
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`s degree and PhD in quantum physics, computer science, electrical engineering, mathematics or a related field Experience in quantum computer programming Experience in applying numerical methods and
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reliability of R-Mode, particularly under varying environmental conditions. Key objectives include understanding the physical processes that affect R-Mode signal propagation, quantifying the variability