At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We’re looking for people who are determined to make life better for people around the world.
Job title: Research Advisor – Computational Biology
Location: UK, Arlington Square, Bracknell
Reports to: Senior Director, Research
Hybrid/Remote: Hybrid

Essential Qualification: -

• PhD in a relevant discipline such as computational biology, bioinformatics, systems biology, computer science with significant Industry and/or academic research experience.
• Extensive experience in analyzing and interpreting large-scale, high-dimensional omics datasets (bulk and single-cell RNA-Seq, spatial omics, proteomics and WES/WGS).
• Proven expertise in applying AI/ML techniques, including deep learning and graph-based approaches, to biological data, with a strong foundation in statistics and data science.
• Proficiency in programming languages such as Python and R, and hands-on experience in ML frameworks (e.g., TensorFlow, PyTorch, and Scikit-learn) and workflow management tools (e.g., Nextflow, Snakemake).
• Experience in deploying and managing bioinformatics pipelines in cloud environments (e.g., AWS, GCP, Azure) utilizing containerization tools like Docker.
• Demonstrated ability to integrate multi-modal biological data and extract actionable insights, contributing to disease understanding, target prioritization, or biomarker discovery in complex disease areas.
• Experience working in multi-disciplinary team and ability to communicate complex ideas and findings to a broader audience.
• Excellent oral and written communication skills

ROLE OVERVIEW

The Genetics and Bioinformatics team within Lilly Neuroscience focuses on analysing large-scale genetics and multi-omics data to uncover complex biological relationships, understand disease mechanisms, disease progression and translating multi-omics insights into actionable targets and biomarkers to accelerate the development of novel therapeutics for neurodegenerative diseases and chronic pain. We are seeking a highly skilled computational biologist with a strong experience in leveraging AI/ML, deep learning and graph networks to drive the integration of genetics and multi-omics datasets. The ideal candidate will have demonstrated expertise in computational biology, with a solid understanding of advanced machine learning methods applied to knowledge graphs.
This role based at our UK Neuroscience Hub in Bracknell, offers the opportunity to lead strategic omics data integration initiatives. The candidate will work as part of a global team of bioinformaticians, statisticians, and data scientists to identify and integrate genomic data across several modalities with genetics to support the identification of novel targets and to understand disease mechanisms. The successful candidate will not only contribute to core discovery programs but will also help shape our long-term AI/ML strategy in neurodegeneration and chronic pain. The overall goal of the role is to discover biological insights that will translate into innovative new medicines for patients.

KEY RESPONSIBILITIES:

• Develop analytical workflows using AI/ML algorithms and graph networks to integrate large-scale genetics and multi-omics data with the aim of gaining mechanistic understanding of disease processes and identifying therapeutic targets.
• Analyse large scale multi-omics data including transcriptomics, proteomics, single cell and spatial transcriptomics data from diverse sources, ensuring data quality and integrity.
• Design and implement predictive models to uncover causal relationship between genotype and multi-layer omics data, characterizing their influence on phenotypic outcomes.
• Spearhead AI/ML initiatives within the team, ensuring the integration of cutting-edge advancements in AI/ML, bioinformatics, and omics technologies to continuously enhance and optimize analytical pipelines.
• Collaborate with cross-functional teams including geneticists, biologists, data scientists, and software engineers to translate complex data into actionable biological insights.
• Communicate findings clearly to both technical and non-technical stakeholders through reports, presentations, and publications.
• Lead collaborations with external multi-disciplinary industry and academic teams.
• Provide support for experimental design and analysis of multi-omic data generated through internal and external collaborations.

Essential Qualification: -

• PhD in a relevant discipline such as computational biology, bioinformatics, systems biology, computer science with significant Industry and/or academic research experience.
• Extensive experience in analyzing and interpreting large-scale, high-dimensional omics datasets (bulk and single-cell RNA-Seq, spatial omics, proteomics and WES/WGS).
• Proven expertise in applying AI/ML techniques, including deep learning and graph-based approaches, to biological data, with a strong foundation in statistics and data science.
• Proficiency in programming languages such as Python and R, and hands-on experience in ML frameworks (e.g., TensorFlow, PyTorch, and Scikit-learn) and workflow management tools (e.g., Nextflow, Snakemake).
• Experience in deploying and managing bioinformatics pipelines in cloud environments (e.g., AWS, GCP, Azure) utilizing containerization tools like Docker.
• Demonstrated ability to integrate multi-modal biological data and extract actionable insights, contributing to disease understanding, target prioritization, or biomarker discovery in complex disease areas.
• Experience working in multi-disciplinary team and ability to communicate complex ideas and findings to a broader audience.
• Excellent oral and written communication skills.