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of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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resolution by integrating plasmonic nanopores with a high-speed Raman detection system, an automated control system, computer simulations, and advanced Raman-based bioinformatics. The RamanProSeq consortium
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complementary contributions to existing research at FIMM and the University of Helsinki more broadly. Successful candidates will hold a doctoral degree in for example data science, statistics, bioinformatics
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of Helsinki. The main research fields at the department are artificial intelligence, big data frameworks, bioinformatics, data analysis, data science, discrete and machine learning algorithms, distributed
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with a second cycle academic degree (MSc, MD or equivalent) in biology, biochemistry, bioinformatics, biotechnology, cell biology, computer science, genetics, medicine, or other related fields, obtained
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drive projects forward -A curious, problem‑solving mindset and interest in new methods -Background in bioinformatics, computational biology, or a related field -Experience with bulk RNA-Seq, ATAC‑seq, and
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analysis (RNA-seq) and associated bioinformatics workflows. ⦁ Histological analysis of tissues, including sample preparation, staining (H&E, immunohistochemistry, or immunofluorescence), and microscopy