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Field
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very challenging. Therefore, high-throughput screening of drug-like molecules needs to also consider their synthetic viability. The aim of this project is to develop a deep learning and generative design
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. A combination of Raman spectroscopy and total X-ray scattering techniques will be used to study the crystallisation of drug molecules and molecular analogues, to determine the influence of functional
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release (2) a stimuli-triggered drug release (e.g. light, pH, etc.). The current PhD project (Design of smart SUstained-RElease drug delivery systems: synthesis, characterization and applications in nano
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Supervisors: Supervisors: Prof. Reinhard J. Maurer (Chemistry/Physics), Prof. Scott Habershon (Chemistry) Summary: The drug discovery pipeline involves the screening of many molecules before viable
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efficiency, drug resistance, high toxicity, long duration of treatment, relapse, inconvenient and painful injections, and the cost. To overcome these limitations, in this project we will employ metal organic
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improving the design and properties of bioportides, this project will, therefore, support therapies to treat unmet medical needs including spinal injuries, Parkinson’s disease, and cancer. PhD investigations
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). There are two joint PhD projects on offer with a start date within 12 months of the PhD scholarship offer letter. The projects cover a broad area of research in the design and synthesis of new
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phenotypes. In this PhD you will address this by a deep learning model of drug responses in cancer. The PhD position focuses on predicting cell type-specific drug responses, identifying transcriptional
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phenotypes. In this PhD you will address this by a deep learning model of drug responses in cancer. The PhD position focuses on predicting cell type-specific drug responses, identifying transcriptional
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for applications that can revolutionise society, including domains such as drug design, agriculture, climate change and more. To cater to applications in these domains, we require fault-tolerant systems that can