AI-Driven Molecular Modelling Fellow

AI-Driven Molecular Modelling Fellow

Full-Time 63000 - 77000 Β£ / year (est.) No working from home possible
Brunel University London

At a Glance

  • Tasks: Contribute to AI-driven molecular modelling and collaborate on groundbreaking research.
  • Company: Brunel University London, a leader in innovative research.
  • Benefits: Gain valuable experience in cutting-edge science and collaborative projects.
  • Other info: Join a dynamic team with opportunities for impactful research and career growth.
  • Why this job: Make a real difference in understanding endocrine-disrupting chemicals through advanced modelling.
  • Qualifications: Experience in protein modelling, docking, machine learning, and Python development.

The predicted salary is between 63000 - 77000 Β£ per year.

Brunel University London seeks a Research Fellow to contribute computational modelling, docking and AI-based analyses for a NERC-funded project on endocrine-disrupting chemicals.

The role emphasizes integrating modelling results with experimental data and cross-institution collaboration.

The successful candidate will have experience in protein molecular modelling, docking, machine learning for computational biology, and Python software development.

AI-Driven Molecular Modelling Fellow employer: Brunel University London

Brunel University London is an exceptional employer, offering a vibrant and inclusive work culture that values diversity and collaboration. Located in Uxbridge, the university provides ample opportunities for professional growth and development, particularly in international engagement roles like the Global Engagement Coordinator. With a commitment to flexible working and a supportive environment, employees can thrive while contributing to meaningful global partnerships and student mobility initiatives.

Brunel University London

Contact Details:

Brunel University London Recruitment Team

We think you need these skills to ace AI-Driven Molecular Modelling Fellow

Computational Modelling
Docking
AI-based Analyses
Protein Molecular Modelling
Machine Learning for Computational Biology
Python Software Development
Data Integration