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adapt advanced machine learning frameworks (SPARKS and CEBRA) for supervised and unsupervised analysis of high-dimensional neural data to decode multisensory information Investigate how neural
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visual and auditory cortices using techniques such as cross-modal decoding, unit reliability analysis, and shared variance component analysis (SVCA) Create comprehensive data visualisations and perform
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been collected in Malawi under a joint agreement with the Government of Malawi, with field phenotype data, genomic sequencing data obtained in the UK, and micro-CT scanning data being also collected
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measurement in construction. The skills, qualifications and experience required to perform the role are: Hold (or be close to obtaining) a PhD in Computer Science, Civil Engineering, Data Science, Information
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of statistics and quantitative data analysis, hands-on experience with R or Python strong interest in prototyping commitment to and interest in the design and implementation of Open Science/Open Source practices
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-based reviews, data collection and analysis, written outputs, and the dissemination of research findings to different audiences, including through investor briefings and academic publications. We
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for 36 month fixed term at 0.6 FTE (22 hours). Key Accountabilites Organising intervention sessions and data collection, including set up, implementation and analysis of the SleepBoost intervention program
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considered. Qualifications/Skills PhD degree in a programme relevant to human-computer interaction and/or critical computing, ideally in Computer Science, Industrial Engineering, Interaction Design, or a
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/College research strategy. 2. Document research output including analysis and interpretation of all data, maintaining records and databases, drafting technical/progress reports and papers as appropriate. 3
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conducting the qualitative interviews with patients and analysing the interview data. You will be presenting that data to the study team at regular meetings and contributing to the intervention and app