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As a Software Developer at the SciLifeLab Data Centre, you will develop and maintain national systems for research data, using Python and Kubernetes to build scalable and sustainable solutions. Join
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knowledgeable system developer for our national DDLS data services, with a profile towards data engineering, systems development, and data management. In this role, you are expected to develop software, systems
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or Apptainer. Experience with software deployment and infrastructure automation, e.g. Ansible, and CI pipelines. Experience with modern software engineering practices, such as code reviews, testing, automated
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expertise in existing methods and state-of-the-art in the field. The position includes algorithm design, software implementation, and validation on experimental datasets. You will contribute to building a
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of approaching reconstruction and variability analysis. The project combines applied mathematics, computational imaging, and structural biology. You will develop algorithms, implement and test software tools, and
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: – Certificate or Diploma verifying your doctoral degree – Verification of leave, if relevant – Documents verifying awards and recognitions stated in your CV, leadership or teaching activities, etc, and other
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of computational tools and software for cancer risk prediction. This position offers the chance to engage in cutting‑edge interdisciplinary research at the intersection of ML and cancer research, and to contribute
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with nano-LCs. Performing data analysis and interpretation using established proteomics software and tools, such as Proteome Discoverer, Spectronaut, Skyline, Byonic, Perseus and R-based Shiny
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). Experience in mathematical modeling of DNA or protein evolution. Hands-on experience with model training (CNNs, transformers, …) and libraries (TensorFlow, PyTorch). Experience in software and method
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at Sahlgrenska Academy of relevance include genomics, metagenomics, culturomics, proteomics, transcriptomics, software development, machine learning, and other statistical analyses of large-scale health data