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School of Engineering Sciences in Chemistry, Biotechnology and Health at KTH Project description Third-cycle subject: Biotechnology The project aims to develop probabilistic deep learning models
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evolution across different genomic regions by developing interpretable and efficient methods in comparative pangenomics, leveraging machine learning methods and statistical analysis (https://cgrlab.github.io
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modeling, machine learning, and AI techniques applied to biomedical data is a plus. Clinical Proteomics: Experience with clinical trial data, real-world evidence (RWE), and biomarker-driven trial designs is
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