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, production-grade machine learning solutions for predictive modelling and complex decision-support systems. Develop scalable and efficient ML pipelines using MLOps best practices. Address challenges related
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-driven insights, and process models). Main Responsibilities: Design and implement a model-based management infrastructure to support integration and harmonization of data and models in a heterogeneous
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research projects and prepare project deliverables Provide guidance to Master students and PhD students who submit work to conferences or journals
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and the successful applicant will be directly supervised by Dr Thomas Raleigh. The project team also includes Dr Laura Gow (Principal Investigator) and Dr Robin McKenna (Co-Investigator) who are both
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. The successful candidate will work in close collaboration with the LCSB core facilities, as well as the Skupin and Heneka groups. Main tasks: Generate mutant and transgenic reporter lines in zebrafish and mouse
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) indicating reference to the subject areas mentioned above Contact information of at least two referees Early application is highly encouraged, as the applications will be processed upon reception. To ensure
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.) · Reporting to the Group Leader Is Your profile described below? Are you our future colleague? Apply now! Educational Background · PhD degree in Physics, Chemistry, Materials Sciences, or a related field
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of recent research and projects Sketch of planned research and publication activities (2 pages each) Contact information of at least two referees Early application is highly encouraged, as the applications
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Applications should include: Curriculum Vitae Cover letter Names of at least 2 reference letter writers Early application is highly encouraged, as the applications will be processed upon reception
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Applications should include: Curriculum Vitae List of publications and manuscripts in preparation (if applicable) Copy of PhD degree certificate, if available Cover letter including: Self-assessment