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of algorithms, machine learning, optimization, scientific software development and high-performance computing. The division is also an important part of the eSSENCE strategic collaboration on e-science and of
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-learning frameworks, such as PyTorch, and high-performance computing (HPC) environments. Knowledge of molecular and cellular biology, systems biology, or precision medicine. Finally, a letter of intent
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-performance computing, particularly in the theory of efficient string and data structures, sequence indexing, and large-scale data analysis. Experience with the Burrows–Wheeler transform, pattern matching, and
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Medicine (WCMTM) and SciLifeLab in the University of Gothenburg. and is tightly connected to a broad network of international collaborators. Duties Develop and perform high-resolution spatial transcriptomics
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development, high-throughput data analysis, and working with large population-based cohorts and clinical biobanks. The student will learn how to scientifically assess the study quality, perform appropriate
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experience of large-scale data management, high-performance computing (HPC), GPU acceleration, and parallel file systems Documented experience in leading staff and operations supporting bioinformatics and
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-scale datasets generated in the Piazza laboratory, public structural proteomics datasets, state-of-the-art mass spectrometry infrastructure at SciLifeLab, and high-performance computing resources
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excellence as evidenced by strong scientific publications and track record relative to career stage. Strong programming skills (Python or R) and familiarity with high-performance computing Preferred
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well as completion of compulsory courses within the doctoral programme. Within the research projects, you will plan studies, collect data, clean the data, perform analyses, interpret results, and present your findings
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steps in workflows and implement optimisations to maximise yield and data quality Gain experience in interpreting sequencing data and performing quality control in close collaboration with computational