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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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available single-cell sequencing data generated from patient samples and mouse models, we will enhance and apply machine-learning based algorithms to deconvolute bulk tumor RNA-seq samples to distinct immune
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of best practices in machine learning and statistical inference. Provides expertise for high level or complex data-related requests and engages other IT resources as needed. Performs other related work as
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NOVA Institute for Medical Systems Biology (NIMSB) announces Four Independent Group Leader positions
for integration of large-scale omics datasets, and application of machine learning and statistical modelling for decipher cell and tissue behaviour, elucidate disease mechanisms, and enable patient stratification
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of machine learning techniques Proficiency using data science tools (e.g., Python, R, MATLAB, MySQL, Jupyter Notebooks) Excellent verbal and written communication skills including the ability to communicate
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artificial intelligence methodologies. The successful candidate will work at the forefront of computational biology, developing novel approaches for large-scale genomic data analysis and contributing
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, ELISPOT, flow cytometry, B and T cell receptor sequencing, and transcriptomics. You will develop a reproducible informatics and machine learning pipeline to process large volumes of sensitive trial data in
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spatial omics datasets. The position will also contribute to multi-modal data integration efforts that combine imaging, genomics, and machine learning approaches. Key Responsibilities Data Processing
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datasets, therefore, there will be a focus in the implementation of models for large volumes of data. The project will work in an exciting interface of statistics and machine learning and has the potential
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with the Control and Automation group at inspire AG. The project is part of a large group effort involving ETH, inspire AG, and ZHAW and brings in multiple engineers and PhD students to continuously