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Field
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in NLP. Completed a PhD or equivalent qualification or research experience in machine learning, natural language processing and image processing. Emerging track record and recognition for quality
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(see below). There is currently one fellowship available where the successful candidate will join one of our Cardiovascular Research Teams, details as follows: - BRC Theme: Cardiovascular / Imaging
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. fluorescence imaging, molecular biology, cell culture, immunohistochemical assays, circuit manipulations, mouse surgery or behavioral assays) and electrophysiological recording (in vivo extracellular recordings
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to established researchers, across machine learning, statistics, logic, language technology, and ethics. You will be also part of the Digital Signal Processing and Image Analysis (DSB) group in the Department
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skills in image processing or genomic data analysis. Proficiency in rodent neurosurgeries. Familiar with Linux OS, virtual environment working and batch scripting. Programming proficiency in R, Python
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responsible for data/image acquisition, analysis and interpretation and for using this information to design efficient heterogeneous photocatalytic processes. This will involve working on the synthesis and
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, develop, and optimize new methods and techniques to address critical project or functional area needs. Participants will improve existing or develop new laboratory methods and processes, read and adapt
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modifiers. The cultures will be analysed using basic molecular and cell biological techniqu es as well as high throughput imaging and analysis to observe modifier effects on LRRK2 and LRRK2 Rab substrate
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strategies that modulate the crosstalk between tumor and immune cells, and develop new image-based screening technologies to identify targets that mediate clinically-relevant cell-cell interactions
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etching. Use ‘zoom’ tomography and imaging to resolve structural variation across scales from 30μm down to 3nm to establish a platform for reverse bottom-up enamel remineralisation. Bottom-up multi-modal 4D