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profile Master's in engineering, computer science, mathematics, physics, biophysics, bioengineering or related discipline Enthusiasm for interdisciplinary research, critical thinking and self-driven
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sequencing, genome-wide data integration, statistical modeling, and hypothesis-driven experimental design, preparing them for leadership roles at the interface of molecular biology and data science. YOUR TASKS
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, the project accelerates trait data acquisition by applying computer vision to herbarium specimens and field photos, as well as large language models to extract complementary information from literature and
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these analyses will guide functional validation using in vitro assays and genetically engineered mouse models to identify signaling pathways that promote differentiation and reduce aggressiveness. The doctoral
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: Department of Chemical & Biological Engineering, Faculty of Engineering Main Supervisor: Professor Sankar Bhattacharya Employment Type: Full-time Duration: 3.5-year fixed-term appointment Remuneration: $36,000
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2 Oct 2025 Job Information Organisation/Company Tallinn University of Technology Research Field Computer science » Programming Computer science » Other Engineering » Materials engineering
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-on monitoring with cutting edge data-driven and physical based models, including the deployment of machine learning algorithms. The project aims to have a tangible impact on the way urban waters are monitored
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and magnetic fields. A crucial aspect lies in the interpretation/modelling of the results. In this role, you will get to work with a variety of devices structures, with an emphasis on quantifying
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-driven changes in rainfall. This poses significant flood risk to homes, businesses and infrastructure. For example, during the winter of 2015/2016, mine water flooding at Kibblesworth in Gateshead flooded
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will develop generally applicable machine learning models and methods driven by the data-rich experiments from our collaborators. The real-world use-case is to learn the rules that govern the dynamics