10 of 10 Transcriptomics Jobs in England

of commit early and deploy often Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience, especially design of data visualisations Knowledge of agent-based approaches (e.g. LangGraph, PydanticAI, AutoGen More ❯

and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and Google More ❯

and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and Google More ❯

and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and Google More ❯

and GitHub Actions - essential Agile Methodology Preferred qualifications: Experience with Docker or containerized applications, especially architecture of multi-container applications Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Knowledge of AI/ML approaches and deployment of AI/ML powered applications - especially using language models or NLP Experience with Kubernetes and Google More ❯

DevOps tools) with a commitment to early commits and frequent deployments.Preferred Qualifications:Experience with Docker or containerized applications, particularly multi-container architecture.Experience with biological or scientific data (e.g., genomics, transcriptomics, proteomics) or pharmaceutical industry experience, especially in designing data visualisations.Knowledge of agent-based approaches (e.g., LangGraph, PydanticAI, AutoGen).If you're looking for a role where your skills will make More ❯

with a commitment to early commits and frequent deployments. Preferred Qualifications: Experience with Docker or containerized applications, particularly multi-container architecture. Experience with biological or scientific data (e.g., genomics, transcriptomics, proteomics) or pharmaceutical industry experience, especially in designing data visualisations. Knowledge of agent-based approaches (e.g., LangGraph, PydanticAI, AutoGen). If you're looking for a role where your skills More ❯

experience with modern software development tools/ways of working (e.g. git/GitHub, DevOps tools for deployment) Preferred qualifications: Demonstrated experience with biological or scientific data (e.g. genomics, transcriptomics, proteomics), or pharmaceutical industry experience Bioinformatics expertise, familiarity with large scale bioinformatics datasets Experience using Nextflow pipelines Knowledge of NLP techniques and experience of processing unstructured data, using vector stores More ❯

decisions. Key Placement Learnings: Perform analyses and build predictive models using R and Python, following coding best practices and using cloud platforms. Process, analyze and integrate scientific data (e.g., transcriptomics, proteomics, assays). Benchmark approaches to compare different algorithms. Interact with laboratory and computational scientists to understand scientific context. Role 2 - Scientific Data Engineering Degree requirements: Physical Science (Chemistry, Engineering More ❯

AI-driven biological discovery and therapeutics. Drive foundational research efforts for the company's biological AI models, including leading projects related to protein-focused foundation models. Requirements PhD in Transcriptomics, Computational Biology, Artificial Intelligence, Machine Learning, or a related scientific field, or equivalent industry experience. Strong programming skills, especially in Python, with hands-on experience using deep learning frameworks such More ❯