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: 30057201; Nature Genetics, in press) and has pioneered novel machine learning approaches for analyzing genomic data (e.g., bioRxiv 517565). The Kübler Lab is integrated into the extensive Berlin research
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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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results. Machine Learning skills to automise comparison process. Unbiased approach to different theoretical models. Experience in HPC system usage and parallel/distributed computing. Knowledge in GPU-based
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experience in the analysis of metagenomics and/or biological high-throughput data Knowledge of statistical and machine learning methods in the context of biological systems Experience with programming (e.g
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: university and, if applicable, PhD degree (e.g. Master/Diploma) in mathematics, physics, materials science or related subjects basic knowledge of computer programming (e.g. Python, Matlab and C++) excellent
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applications. Our overarching aim is to obtain a holistic view of interconnected biological systems in health and disease. We develop clearing technologies for cellular-level imaging and deep learning algorithms
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control software and machine learning expert. How you will support us: ▪ You will take on responsibilities in the field of control and operation of high-coherence superconducting quantum circuits, with a
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from the vibrant research 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
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Dortmund, we invite applications for a PhD Candidate (m/f/d): Analysis of Microscopic BIOMedical Images (AMBIOM) You will be responsible for Developing new machine learning algorithms for microscopy image
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processing, time series analysis or machine learning for the interpretation of structural data is desirable. Basic knowledge of numerical analysis and design of structures for special load cases (earthquakes