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Field
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highly desirable but not necessary as training will be provided. Experience of computer modelling is desirable but not essential as full training will be provided in an active and well-resourced research
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process is poorly recorded and needs improvement. Aims and Objectives In collaboration with the Health Innovation Partnership, a modelling pipeline will be devised to cope with the challenges of data
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including predictive modelling, computer vision and epidemiology. The student will join an established team of investigators, including statisticians, epidemiologists, image scientists, and clinicians
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will generate a wide range of contemporary high-resolution next-generation sequencing and array-based genomic and epigenomic datasets across large cohorts of human tumours and experimental models
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natural language processing, Dr Matthew Hitchings, who will offer cutting-edge insight into high-throughput sequencing and a strong background in comparative genomics and bioinformatics and Professor Lewis
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of the most common malignancies in women. Particularly, triple negative breast cancer (TNBC) has a high rate of recurrence and is more challenging to treat due to the absence of oestrogen receptor, progesterone
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| £20780 + £2500 industry top up (per annum (tax free)) Overview This exciting, fully-funded PhD opportunity invites applications from candidates with a robust foundation in data science, modelling, and
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. The system will leverage cutting-edge techniques in Natural Language Processing (NLP), Machine Learning (ML), and Multimodal Analysis to conduct adaptive interviews, assess candidate responses, and generate
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invites applications from candidates with a robust foundation in data science, modelling, and/or engineering, and a keen interest in deploying data analysis and artificial intelligence (AI) to solve real
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process conditions. Furthermore, this research will focus on the development of a model, allowing for virtual testing and optimisation of the chemical recycling process. This includes potential