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fundamental drivers of metastasis, drug resistance, and other key cancer outcomes. Projects will be tailored to the candidate’s strengths and interests, with multiple creative, high-impact directions available
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· Gender-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
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spanning multiple diseases. About the lab: The Glastonbury Lab is focused on developing and applying Machine Learning to problems in digital pathology and spatial transcriptomics. The group has a particular
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contributing to specifically the area of handling spatial data to assess the distribution of several soil properties and fungal communities using samples collected from multiple habitats and land use types at a
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, ultimately, will lead a multidisciplinary team focused on the study of rhabdomyosarcoma. Multiple projects are available, focused on the reciprocal interaction between tumor cells and the extracellular matrix
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compensation is based on multiple variables. This range represents annual salary only and does not include supplemental performance-based pay or any one-time payments that eligible candidates may be offered
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· Gender-friendly environment with multiple actions to attract, develop and retain women in science · 32 days’ paid annual leave, 11 public holidays, 13-month salary, statutory health insurance
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and in vivo model systems, applying multiple omics methods. You will be working with clinical samples, method development and several molecular biology techniques, especially PCR and sequencing as
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have performed such studies for a long time and successfully discovered multiple new drug effects under this umbrella. Specifically, this position will work with generating signals within the domain
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research is based on large and high-dimensional datasets across multiple modalities, including molecular, clinical and histopathology imaging data. Our computational pathology research is based