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intelligence. This PhD project will leverage the power of field-programmable gate arrays (FPGA) to deploy machine learning models on the edge with low latency and high energy efficiency. This added intelligence
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. You will draw on ideas from Bayesian optimization and Bayesian deep learning, generative modelling, high throughput screening, and combinatorial synthetic chemistry. Responsibilities and qualifications
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with colleagues at DTU and IIT Bombay, as well as with academic and industrial partners globally. The main purpose of this PhD position is to develop, implement and assess machine learning models
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R Experience with single-cell RNA-sequencing, in particular analysis of data would be an advantage Experience with mouse models and possession of a FELASA B certificate would be an advantage as both
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components are in use. More specifically, the PhD position will look towards connecting different advanced software tools (of multi-physics and data-based models) simulating the metal AM process
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biopsies and advanced, preclinical models. A combination of wet-lab and computational biology, close ties to the clinic, and a wonderful team of early career scientists give us the agility and expertise
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Foundation Models initiative . The proposed starting date is 1 September 2025 or soon thereafter. The appointment will be made for a term of three years at a competitive salary and will follow the PhD study
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with the aim of making it a practical computational tool in the near term. The project will focus on Gaussian Boson Sampling (GBS), which is a specialized photonic quantum computing model with