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Join MultiD Analyses AB and the University of Gothenburg to develop innovative bioinformatics and machine learning methods for RNA Fragmentomics, with the ambition to improve cancer care through
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Requirements A doctoral degree in bioinformatics, computational biology, cell biology with a strong computational component, or a closely related field. This eligibility requirement must be met no later than
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biology and bioinformatics, microbiology and immunology, molecular biology, molecular biophysics, molecular evolution, molecular systems biology, and structural biology. While the foundation of our research
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biology: how sex chromosomes evolve, and what shapes sex ratios in natural populations. You will work with cutting‑edge methods in population genomics, bioinformatics and modeling, alongside a bit of hands
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measurements. Have a background in computational biology, bioinformatics, or machine learning for biological problems. Have experience with modern deep learning frameworks (PyTorch, JAX, or equivalent). Have
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, DNA–protein conjugation, cell culture, high-throughput sequencing and bioinformatics. During the doctoral education the student will design and run experiments, analyse and interpret data. We value
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communication and collaboration skills Nice to have: Background in bioinformatics or biology Experience working with biological or medical data Curiosity and willingness to learn are highly valued. Requirements
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including epidemiology, statistics, bioinformatics, and cancer biology. We have both “dry lab” and “wet lab” components. Currently the group consists of 2 postdoctoral researchers, 1 statistician (part-time
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working across plant biology, including molecular biology, genomics and bioinformatics. UPSC provides advanced infrastructure for sequencing, single-cell technologies and experimental plant research, as