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Read more and apply SciLifeLab / Careers / PhD student in Machine Learning with a focus on mathematical and statistical methods for uncertainty quantification Uppsala University, Department of
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comparative pangenomics, leveraging machine learning methods, statistical analysis and efficient algorithm and data structures ( https://CGRlab.github.io/research/ ). About the research project We are open
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experts in data science, machine learning, and artificial intelligence, to support excellent research projects and engage in advanced mentoring and postgraduate training on a national level. As part of
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workday might involve writing and running code to process sequencing data on a computer server, applying statistical models and machine learning algorithms, and performing downstream data analysis
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work, you will develop predictive and biologically interpretable models that connect molecular patterns across multiple scales of human biology. The project lies at the interface of artificial
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of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, computer science, scientific computing, mathematics, statistics or a related field
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a Master’s degree in computer science, image analysis and machine learning, engineering physics, data science, applied mathematics, molecular biotechnology engineering, or another related field; or
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taking part in the supervision of students. A limited amount of teaching may be included (max 20%). Requirements PhD degree in machine learning, scientific computing, statistics, physics or a related
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Doctoral (PhD) student position in selection of DNA/RNA nanostructures as novel therapies Karolinska Institutet Share: Facebook Twitter LinkedIn Email Application deadline August 5, 2026 Read more and
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(National Bioinformatics Infrastructure Sweden: www.nbis.se ) to help shape and accelerate the adoption of advanced machine learning and AI in data-driven Life Science research. At the SciLifeLab