Principal Computational Biologist

The company is a clinical‑stage drug discovery biotech company translating condensate biology into innovative medicines. Biomolecular condensates are reshaping our understanding of biology, and our highly collaborative team is working to turn these insights into breakthrough therapies for some of the toughest diseases. We are seeking an exceptional Principal Computational Biologist with deep expertise in multi‑omics data analysis to support our drug discovery and development programs. In this role, you will work closely with biologists and chemists to translate complex research questions into well‑designed omics studies, and you will lead the design, execution, and interpretation of bioinformatics analyses that inform program decisions. In this role, your key responsibilities will be: Working with bench science colleagues to translate research questions into appropriate experiments and bioinformatics analyses Designing and implementing new computational approaches to analyze ‘omics data in ways that address novel questions arising in our discovery and development efforts Running and refining bioinformatics analyses and pipelines for the analysis of ‘omics data, particularly RNA‑seq, proteomics, phospho‑proteomics, and WGS data Integrating literature and other datasets, such as pathway / network databases, to derive biological insights and get to ‘so what’ results Synthesizing and communicating results effectively to colleagues, and iteratively refining methods based on their feedback Owning delivery of bioinformatics workstreams end‑to‑end, potentially including the mentoring and coaching of junior colleagues Continually learning and growing as a bioinformatician, identifying emerging methods and tools to implement where appropriate Contributing to developing bioinformatics and data science understanding, capabilities, and standards across the organization Role Qualifications: A PhD in a relevant computational field such as Bioinformatics, Computational Biology, Genomics, or a related discipline 4+ years of industry experience (in pharma or biotech) post‑PhD in computational roles, with demonstrated impact Proficiency in R and/or Python, with a high level of comfort in data manipulation and analysis Hands‑on research experience with bulk transcriptomic data, ideally also with experience of single‑cell, proteomic, phospho‑proteomic, and genomic data Expertise in statistical methods for ‘omics data analysis, particularly for RNA‑seq and proteomics datasets (e.g., differential gene, gene‑set, and pathway‑level analyses), including quality control methods Experience integrating ‘omics data with pathway/network datasets to draw biologically meaningful insights Solid understanding of molecular biology principles, ideally within a research or drug discovery setting Outcome‑driven approach with the ability to explore alternative methods pragmatically while prioritizing high‑impact solutions Collaborative and communicative style, adept at working with colleagues across varying levels of expertise and seniority Beneficial: Experience with analysis of biomarker data from ongoing clinical trials Experience working in drug discovery programs in oncology, neurology, and / or metabolism Experience working in the cloud (AWS) and with code management tools (Git) in collaborative team environments, including with containers and workflow orchestration tools such as Nextflow Experience working with knowledge graph Experience training and working with machine learning models #J-18808-Ljbffr Barrington James