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using geographic information systems (GIS) and programming languages (e.g. Matlab, Python, R) and working with large data sets and data formats, such as netCDF, HDF, including analysis tools such as NCO
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Fritz Haber Institute of the Max Planck Society, Berlin | Berlin, Berlin | Germany | about 1 month ago
associated with the Ultrafast Nanoscience group of Prof. Ralph Ernstorfer at TU Berlin. Requirements Successfully completed PhD degree in physics or a related subject. Excellent communication skills, and in
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close collaboration with international and national partners You will analyze and integrate various types of generated data (e.g., next-generation sequencing, large-scale genomic, transcriptomic
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with fewer data points and tailored reward functions towards design objectives while generating molecules in 3D. Additional requirements: Doctoral degree (PhD) in computational (medicinal) chemistry
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the world. We are seeking a highly motivated Postdoctoral Researcher with expertise in large-scale omics data analysis to establish an innovative multi-omics data integration workflow. This unique position
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12 Mar 2025 Job Information Organisation/Company Technische Universität Ilmenau Department Human Ressources Research Field Mathematics Researcher Profile Recognised Researcher (R2) Positions PhD
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Heidelberg University and Stanford University, including population health researchers, clinicians, and methodologists. The researcher will lead analyses in large-scale electronic health record data
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-sampling data. Furthermore, the position holder will play a central role in creating high-quality training datasets (seagrass maps) to support artificial intelligence (AI) algorithms used in related projects
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at both large and small scales. The scientific evidence-based knowledge developed in ISOLUME will be used to develop a roadmap for implementing changing marine lightscapes as an indicator in management
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-of-the-art computational infrastructure and proteomic data to address fundamental biological questions. Key Responsibilities: Develop and apply computational workflows to analyze large-scale proteomic datasets