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for support in technology development. You will work closely with a PhD researcher at the German partner who focuses on the underlying machine learning models, and you will help coordinate the joint work across
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demonstrable experience with programming in Python and implementing statistical or machine learning algorithms. You have experience with software development practices such as testing and version control with
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Physics Informed Machine Learning method which exploits the advantages of physics-based and data-driven models, while mitigating the disadvantages. This research will contain experimental and modelling
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Design and build flow setups using 3D printer, pumps, valves operated by a computer and the corresponding software. Develop flow cells to connect various spectroscopic tools to the setup. Create and
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, pumps, valves operated by a computer and the corresponding software Develop flow cells to connect various spectroscopic tools to the setup Create and validate reproducible automated workflows
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structure modeling in cancer immunotherapy design. Profile A — AI PhD in machine learning, computer science, computational science, or a related field. Strong experience with deep learning (e.g., PyTorch
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metabolomics, lipidomics, proteomics and genomics, and combine these data using statistical and machine-learning approaches. Established markers such as neurofilament light chain (NfL) and GFAP will provide a
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), Computer Science (Machine learning, Efficient Algorithms and High Performance Computing), and Physics (Image Formation Modelling). Your project is part of the DUAL-IMPACT project, which focuses on the development
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; profile root and leaf microbiomes using amplicon sequencing; analyse integrated microbiome and phenotyping datasets; contribute to machine-learning models predicting pathogen invasion success and plant
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machine learning for molecular and material design; quantum computing for bioinformatics; quantum approaches for safe and sustainable molecular design; and benchmarking quantum simulations of materials