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using liquid biopsy next generation sequencing data for cancer diagnostics. About You Must have a strong background in next generation sequencing data analysis/machine learning, cancer and/or genome
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this paradigm by quantifying antibiotic action at single-cell resolution. The scientific aim Our laboratory has established a large-scale live-cell imaging platform that tracks hundreds of millions
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responses (e.g., differentiation, vascularization, and cell–cell communication). Will design genetic circuits and assays; collect and analyze data using techniques such as flow cytometry, RT-qPCR, next
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the day) to accommodate your needs. Working remotely is possible for up to 1 day/week. About the Role The post is funded for 3 years and is based in the Big Data Institute, Old Road Campus, Oxford
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; mechanism design and institutional design; cooperative AI and multi-agent systems; the study and development of large language models; cross-cultural psychology and large-scale behavioral data; philosophy
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computing, machine learning for hardware design, integrated circuit design, or hardware–software co-design. Experience with semiconductor design tools, circuit/system modeling, or large-scale hardware design projects
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must be fluent in English (written and spoken) and have experience with large-scale health data and epidemiological or related analytical approaches and methodology. Some experience with programming and
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this paradigm by quantifying antibiotic action at single-cell resolution. The scientific aim Our laboratory has established a large-scale live-cell imaging platform that tracks hundreds of millions
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skills in R and/or Python and experience in statistical modelling of high-dimensional biological data. Experience working in HPC environments and managing large-scale sequencing datasets is essential
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comparative research across Mojo, Julia, Rust, and vendor toolchains. Basic Qualifications: Ph.D. in Computer Science, Computer Engineering, or related field. Experience with LLMs or agentic AI frameworks