(Senior) Scientist, Chemoproteomics

British Mass Spectrometry Society (BMSS); London; On-site; GBP 45,000 - 80,000

Job description

We are seeking a Senior Scientist in Chemoproteomics to lead, develop, implement, and optimise cutting-edge experimental methods for mapping proteome-wide small-molecule interactions. The successful candidate will design and execute high-throughput chemoproteomics experiments, work closely with a strong AI team to develop predictive models, and contribute to the creation of an interactive platform to share and analyse proteome-wide interaction data.

Key Responsibilities

1. Chemoproteomics Strategy & Experimental Execution
   Develop and optimise chemical proteomics workflows for large-scale identification of small-molecule interactions with intrinsically disordered proteins.
   Apply photoreactive and bioorthogonal probes to map interactions in intact cells.
   Utilise quantitative mass spectrometry (LC-MS/MS, TMT-based proteomics) to analyse small-molecule–protein interactions.
   Expand fragment-based ligand discovery (FBLD) approaches to intrinsically disordered and challenging proteins.
   Stay up to date with advancements in chemoproteomics, disordered proteins, and mass spectrometry, and translate these developments into novel experimental and analytical approaches.
   Contribute to the design and execution of innovative mass spec-based research projects, particularly through the integration of AI and mass spec methodologies to advance Bind’s scientific objectives.
2. Team Collaboration and Training
   Collaborate with computational scientists to build a predictive ligand discovery platform.
   Mentor and support Bind’s interdisciplinary team in experimental design, execution, and data interpretation.
   Train team members in chemoproteomics workflows, mass spectrometry techniques, and analysis.
3. Capability & Infrastructure Development
   Establish and manage collaborations with external mass spectrometry labs in Central London, ensuring seamless access to off-site proteomics workflows.
   Serve as the primary liaison for mass spec facility partnerships, coordinating sample preparation, data acquisition, and analysis with external teams.

Qualifications and Expertise

Education

• PhD in Biology, Chemistry, Biochemistry, or a related field with a specialisation in (chemo-)proteomics and/or mass spectrometry.

Skills and Experience

• Hands-on experience with quantitative proteomics (TMT, SILAC, label-free quantification) and LC-MS/MS methods.
• Expertise in photoaffinity labelling, bioorthogonal chemistry, and fragment-based ligand discovery (FBLD).
• Experience with small-molecule screening approaches for protein interaction studies.
• Expertise in mass spectrometry data processing pipelines (MaxQuant, Proteome Discoverer).
• Experience integrating multi-omics datasets.

Nice to have

• Experience working with intrinsically disordered proteins.
• Experience working with data visualisation software (Perseus).

Additional Attributes

• A creative mindset with a passion for advancing mass spectrometry.
• Enthusiasm for training and mentoring team members at all levels of mass spec expertise.
• A collaborative approach, with a willingness to engage in team-based research initiatives.
• Commitment to continuous professional development in mass spec.
• Passion for contributing to the establishment and growth of a world-class research organisation.

Further Information

Bind Research is an innovative not-for-profit research organisation at the forefront of developing tools and datasets to characterise small-molecule interactions with intrinsically disordered proteins. Based in central London, Bind leverages interdisciplinary methods spanning chemoproteomics, experimental biophysics (NMR spectroscopy), and computational approaches. You will play a crucial role in shaping the future of this cutting-edge research initiative from the beginning.

Join Bind Research to push the limits of drug discovery for intrinsically disordered proteins through large-scale chemoproteomics, experimental biophysics, and AI-driven ligand prediction.