Computational Structural Biologist; ACBI-Glue Team - UOD

Computational Structural Biologist (ACBI-Glue Team) - UOD
2067

Posted on 3 December 2025 | Reference: UOD
2067

The Ciulli Research Group at the Centre for Targeted Protein Degradation (CeTPD) is seeking a talented Computational Structural Biologist with expertise in protein structures and protein complexes. This role will focus on predicting protein-protein interactions and enhancing structural biology data generation and processing, including the application of machine learning and generative AI.

Join a newly established research team collaborating with Professor Alessio Ciulli FRS and Boehringer Ingelheim to develop molecular glue degraders targeting cancer. The project aims to: (1) identify and characterize ubiquitin E3 ligases for target recruitment using cellular and computational methods; (2) elucidate interactions through structural and biophysical studies of recombinant proteins in vitro; and (3) screen small molecules that enhance these interactions to function as  molecular glues.  

Our objective is to create innovative, structure-driven methods for the de novo design of glue degraders targeting hard-to-drug proteins, ultimately accelerating novel cancer therapeutics for patients.

As part of the newly formed  ACBI-glue team,  you will operate in state-of-the-art laboratories at the University of Dundee's CeTPD ( ), working on the identification, validation, and characterization of protein-protein interactions and their screening to identify enhancing small molecules. These molecules will serve to recruit ubiquitin E3 ligases, facilitating the intracellular ubiquitination and degradation of disease-associated target proteins.

You will predict structural features of interactions between target proteins and E3 ligases, validating these through experimental and in vitro biophysical studies. The role entails conducting advanced predictions and simulations to provide insights to synergise with structural investigations by cryo-EM and/or X-ray crystallography. Collaboration is key; you will work closely with the Principal Investigator, Senior Lead Scientist, fellow postdoctoral researchers, and researchers across the Ciulli academic groups and other drug discovery teams within CeTPD, as well as our industry partner.

Candidates should demonstrate excellent communication and collaboration skills essential for multidisciplinary drug discovery initiatives. This position represents a unique opportunity to join a dynamic team at a world-renowned Research Centre focused on pioneering translational chemical biology and drug discovery approaches in targeted protein degradation and related modalities.

Candidate Requirements:

• Ph.D. in structural biology, computational chemistry, biophysics, computer science, or a related discipline.
• Proficient in using and optimizing structural computational biology tools, including AI/ML software (e.g., Alpha Fold, Boltz) and modern cryo-EM processing software (e.g., CryoSPARC, Relion).
• Experience in conducting computational research with structural biology data and effective teamwork.
• Scientific programming skills, with the ability to support non-technical team members.
• Excellent interpersonal, communication, and presentation skills.
• Independent planning and work capabilities within a diverse team.
• Strong time management, organizational, and motivational skills.
• Collaborative approach to science.

Preferred skills:

• Experience in molecular dynamics simulations for protein interaction analysis.
• Familiarity with high-performance computing environments and large data management.
• Interest in cancer-related pathways and gene regulatory networks to enhance drug discovery efforts.
• Available as soon as possible, for a fixed-term period of 2 years.
• Salary:
  Grade 7 scale (£37,174 - £45,413), commensurate with experience.

Location:

• CeTPD, 1 James Lindsay Place, adjacent to the Life Sciences Complex.

Contact: For more information, please reach out to Professor Alessio Ciulli at [email protected].

Monday, 5 January 2026, 23:59