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Start date: 1 July 2026 or as soon as possible thereafter. Part time, fixed term: Two months at 0.5 FTE (but can be flexible between 1 month at 1FTE and 6 months 0.16 FTE) Applications are sought
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enrichment (GO, KEGG), network analysis, genome assembly and binning, systems biology, and multi-omics integration. Apply statistical modelling, machine learning, and deep learning approaches for biomarker
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pipelines for genomic data analysis, and of programming languages such as R, Python, or Bash script is essential, as is experience of working with High Performance Computing. Time management skills
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research background. • Strong organisational skills. • Experience in qualitative research, including interviewing and data analysis. • Show proven ability to work effectively both independently and
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Fellow or Research Engineer with strong expertise in Human-Computer Interaction (HCI) and social science methodologies to lead the user research and policy development, as part of an interdisciplinary team
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for the position(s) include: Contributions to the ePIC Silicon Vertex Tracker, through software and simulation work and/or hardware development Data analysis for the ALICE or sPHENIX experiments AI/ML research in
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. Laboratory experience in cell culture and molecular biology techniques are essential. Expertise in general areas of stem cell biology and DNA/RNA/Protein isolation/analysis, would be desirable
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. The post-holder will be responsible for bringing forward an innovative programme of work to investigate the impact of the OptiMAx programme through mixed-methods process evaluation and gender analysis
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, Effects, and Criticality Analysis (FMECA), functional FMECA, advanced sensing techniques, sensor and operational data fusion, data analytics, and machine learning algorithms for condition monitoring, fault
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this exciting role, you will focus on the annotation and analysis of genomes from protists and other microbial eukaryotes. This work integrates multi-omics data and involves benchmarking and developing methods