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Senior Scientist / Group Leader on Bioinformatics / Computational Biology on RNA Regulation in Disea
studies Apply machine learning to uncover novel mechanisms and therapeutic insights Mentor junior scientists, contribute to grant writing and publications, and drive the lab’s scientific vision Apply
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in high-performance computing, materials chemistry, theoretical chemistry, molecular dynamics, data science, and machine learning are beneficial. What we offer: We offer a position with a competitive
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areas such as astrophysics, data science, machine learning and high-performance computing scientific leadership and project management of a research group (at least 5 research associates), including
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community around machine learning of the SCADS.AI center (https://scads.ai ) and the recently granted Excellence Cluster REC² – Responsible Electronics in the Climate Change Era. We aim to attract the best
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multi-omics data integration and the project will provide opportunities to learn, develop, and apply machine learning and deep learning methods on genomics data. Requirements: excellent university and PhD
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a collaboration between five Helmholtz Centers (MDC, GFZ, AWI, DESY, HZB), the Berlin Institute for the Foundations of Learning and Data (BIFOLD), and three Berlin universities. To strengthen our team
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Programme is a scientific visitor scheme designed to provide early-career students/researchers (prior to embarking on a PhD) with a passion for technology and tool development an opportunity to gain hands
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maintain pipelines for the analysis of high-throughput sequencing data, including RNA-seq, ChIP-seq, ATAC-seq, and single-cell and spatial omics. Integrate machine learning and large language models (LLMs
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statistics, bioinformatics, machine learning and AI applications. Experience in a number of these technologies is expected. Collaborations within the Cluster of Excellence ImmunoSensation and with other intra
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advanced statistical/chemometrics and machine learning tools, iv) to couple metabolome data with other omics datasets (e.g., genomics, lipidomics, metallomics, and others). Main target areas are drug