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approved drugs that target key dysregulated pathways/proteins in virally infected cells. The candidate will also assist with the development of liver and/or brain organoid cultures including iPSC-based
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of protein-based materials and biocatalysts using synthetic cells. A key objective is the bottom-up construction of synthetic cells that are capable of sustained protein production. This is a formidable
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to projects focused on understanding the molecular and cellular mechanisms underlying metabolic disease, with a particular emphasis on protein trafficking, signalling pathways, membrane transport, proteomics
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and couples these to biological assays. The group is part of the Division of NanoBiotechnology within the Department of Protein Science and we are located at SciLifeLab in Solna. Qualifications
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Jerzy Haber Institute of Catalysis and Surface Chemistry, Polish Academy of Sciences | Poland | about 1 month ago
Employment mode: Full-time Weekly working hours: 40 Employment start date: 2026-10-15 Keywords: biomaterials, microbiology, proteins, materials engineering, biopolymers, physicochemical characterization
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proteins and their complexes with host receptors and antibodies, biophysical and biochemical analyses to complement structural results, and collaborations with virology and immunology labs to understand
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: Mechanistic studies of how m6A alters RNA:protein interactions across the transcriptome Defining the roles of m6A and RNA-binding proteins in brain development, neural function, and neurological disease
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antibody-drug conjugates (ADCs), molecular imaging agents, and targeted therapeutics to improve cancer diagnosis and treatment. We combine protein engineering, chemical biology, molecular imaging
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from multiple departments. The aim is to develop and apply multimodal 3D imaging and analysis frameworks to quantify tissue architecture and protein expression in paraffin embedded tissue samples
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develop and apply multimodal 3D imaging and analysis frameworks to quantify tissue architecture and protein expression in paraffin embedded tissue samples at scale. By integrating AI-drive image analysis