Scientist - Characterization of Biologics LC-MS

Enara Bio is shining a light on Dark Antigen and T-cell biology to develop cancer immunotherapies designed to improve treatment outcomes for broad populations of cancer patients with solid tumors. Our pioneering EDAPT platform enables us to discover cancer‑specific antigens, including HLA‑presented and cell surface antigens, from previously uncharted genomic dark matter. The result is a growing library of Dark Antigens that can address the need for novel, cancer‑specific targets in solid tumors.

Through our proprietary EnTiCE platform, Enara is developing novel bispecific T cell engagers against Dark Antigen targets that are highly prevalent and homogenously expressed across solid tumors.

Based in Oxford, UK, Enara Bio is backed by a strong syndicate of life science investors including RA Capital, Pfizer Ventures, M Ventures, Samsara Bio Capital, SV Health Investors, and the Francis Crick Institute.

Enara Bio has established a best‑in‑class pipeline for the identification of novel, previously undiscovered antigens for development of immunotherapies, using mass spectrometry (MS)‑based proteomics and immunopeptidomics. We have recently broadened the application of MS to include the characterisation of biologics and are looking to increase internal capabilities in this area.

We are looking for a highly motivated scientist to join our team who has a passion for MS‑based proteomics applied to the exciting field of immuno‑oncology. The successful candidate will help in the generation of proteomics data to support the characterization of Enara Bio's novel biotherapeutics as well as supporting our ongoing antigen‑discovery pipeline. This role will make a major contribution in supporting our goal of delivering impactful therapies that make a meaningful difference to patients suffering from cancer.

The successful candidate will work closely with key internal and external stakeholders including academic and non‑academic partners in immunobiology, biochemistry, protein characterisation and LC/MS‑based disciplines. Enara Bio actively promotes a multidisciplinary collaborative approach to working, therefore effective communication is essential to this role as you will be expected to effectively communicate with our collaborators about our scientific research objectives.

• Provide technical leadership on various proteomics analytical workflows with experience in different LCMS based proteomic methods (DDA, DIA, P(M)
  RM and intact mass spec)
• Drive the protein characterisation pipeline by applying various LC‑MS based techniques for our lead biotherapeutic products
• Support the existing immunopeptidomic and proteomic activities including the discovery and validation of targets by LC‑MS
• Provide input for continuous development of MS‑based proteomics and immunopeptidomic methodologies by working cross‑functionally with Enara’s protein characterisation and computational biology teams
• Provide technical expertise supporting the maintenance and troubleshooting of the LC‑MS instrumentation
• Analyse, interpret and clearly communicate data to various stakeholders to support discovery and validation campaigns
• Contribute to a vibrant and innovative working environment where improvements and new ideas are adopted and freely shared among the teams

• Ph.D. (or equivalent experience) in a relevant scientific discipline such as MS‑based proteomics
• In-depth technical expertise in LC‑MS based proteomics and related sample preparation

• A track record of working independently and with the ability to design and execute experiments supporting the characterisation of biologics (Peptide fingerprint mapping, PTM analysis, disulfide bridge mapping and host cell proteomics (HCP) analysis etc)
• Proven ability to develop and maintain high resolution LC‑MS instrumentation and use of proteomics software tools (such as PEAKS, DIANN, Skyline etc)
• Demonstrated expertise using a relevant programming language (for example R) for data interrogation and analysis to support complex proteomics workflows and drive data‑driven decision‑making.
• Experience with sample…