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controlling these molecular networks in vivo . This will be achieved using scRNAseq, spatial transcriptomics, advanced machine learning approaches, and genetic approaches to manipulate the expression of
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successful you will need: Explicitly address each selection criteria MSc/PhD in Computational Biology, Bioinformatics, Computer Science, or a closely related field with a strong focus on machine learning and
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strong focus on machine learning and deep learning applications. Demonstrable experience in developing and implementing deep learning tools, particularly in the context of large-language models
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of snapshots taken with high-throughput super-resolution microscopy and are looking for a Postdoctoral Researcher with a background in machine learning. About the position/ the research project The overall aim
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, Bioinformatics, Computer Science, or a closely related field with a strong focus on machine learning and deep learning applications. Demonstrable experience in analysing large-scale single-cell genomic data
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. UKF jobticket UKF Your challenges: develop and optimize high-throughput analysis pipelines integrate complex RNAseq, Whole Exome Sequencing and TCR repertoire high-throughput data apply machine learning
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electron microscopes, nuclear magnetic resonance machines and other imaging instruments, a class 100 cleanroom for nanofabrication, a series of research vessels to explore the Red Sea, and much more. They
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required: Experience with developing bioinformatic tools (webserver/package) Experience with machine learning Strong background in molecular/cellular biology Experience with analyzing large and complex
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programming skills Experience with developing machine learning models, probabilistic modeling or other bioinformatic tools Any of the following features are highly desirable, but not strictly required
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learning engineers. Your main tasks will encompass the development of novel machine and deep learning algorithms to understand, predict, and treat human disease. Using multi-modal genomic, image, and patient