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for a researcher who can work independently with complex longitudinal data, contribute to a clearly defined publication pipeline, and engage in methodological discussions within a collaborative research
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. Postdoctoral Researcher Position Job Description: The successful applicant will undertake part of the microbial biopesticide discovery pipeline against mosquitoes and pathogens they transmit. He/She will work
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German Cancer Research Center in the Helmholtz Association (DKFZ) | Oettingen in Bayern, Bayern | Germany | 3 months ago
generation of translation-oriented medical and clinical scientists and establishes strong pipelines towards clinical cancer research and the economy. For the Institute of Molecular Oncology and Functional
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components themselves, including the design of retrainable pipelines, model-wrapping services, LLM prompting logic, data pre/post-processing components, and explainability hooks. As a postdoctoral researcher
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2026 Group or Departmental Website: https://mellab.stanford.edu/(link is external) https://spoglab.stanford.edu/(link is external) How to Submit Application Materials: To apply, please submit
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models and analysis pipelines for real-time performance, enabling adaptive imaging and feedback control Design active-learning and retraining strategies to robustly generalize to new microbial communities
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delves into software design concerns, focusing on the internal structure and evolution of AI-enabled components themselves, including the design of retrainable pipelines, model-wrapping services, LLM
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. The postdoctoral associate will be expected to work both collaboratively and independently on research projects, advancing computational methods using machine learning, developing automated pipelines for data
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modelling of high-dimensional datasets. Experience in basic computational methods (e.g. R, Python, and/or other programming languages) Experience in developing computational analysis pipelines Experience with
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linked to oral health outcomes and health disparities. Apply and develop bioinformatic pipelines, statistical models, and computational tools to assess associations between microbial composition, oral