Application Guide

How to Apply for PhD Studentship: Machine Learning-Accelerated NMR Platform for Viral RNA Polymerase Inhibitor Discovery

at University College London (UCL)

🏢 About University College London (UCL)

University College London (UCL) is a world-leading multidisciplinary university consistently ranked among the top 10 globally, with the London Centre for Nanotechnology representing a unique collaboration between UCL and Imperial College London. This specific studentship offers access to cutting-edge NMR facilities and machine learning infrastructure while working directly with Prof. Finn Werner and Dr. Christopher Waudby, both recognized experts in RNA polymerase research and NMR methodology.

About This Role

This PhD studentship involves developing an integrated platform combining fluorine-based NMR spectroscopy, robotic automation, and active learning algorithms to discover inhibitors targeting viral RNA polymerases, with applications to both RNA viruses and DNA viruses like African Swine Fever Virus. The role bridges computational machine learning with experimental biochemistry, requiring the candidate to work at the intersection of structural biology, drug discovery, and artificial intelligence.

💡 A Day in the Life

A typical day might involve morning computational work developing or refining active learning algorithms for NMR data analysis, followed by afternoon laboratory sessions conducting fluorine-based NMR experiments with purified RNA polymerase samples. The role would regularly include meetings with both computational and experimental supervisors to integrate findings and adjust the ML-NMR platform development.

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Interview Prep

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🎯 Who University College London (UCL) Is Looking For

  • Strong background in computational chemistry, machine learning, or bioinformatics with demonstrable programming skills (Python/R) and experience with ML frameworks
  • Practical laboratory experience in biochemistry, molecular biology, or structural biology techniques, particularly NMR spectroscopy or protein purification
  • Understanding of virology, enzymology, or drug discovery principles, with specific interest in RNA polymerases or antiviral development
  • Ability to integrate computational and experimental approaches, with evidence of interdisciplinary research experience

📝 Tips for Applying to University College London (UCL)

1

Explicitly connect your previous research experience to both the computational (ML/algorithms) and experimental (NMR/biochemistry) aspects mentioned in the project abstract

2

Reference specific publications from Prof. Werner's lab (RNA polymerase research) and Dr. Waudby's lab (NMR methodology) to demonstrate your understanding of their work

3

Highlight any experience with automation, robotics, or high-throughput screening methods relevant to the 'robotic automation' mentioned in the project description

4

Discuss both RNA viruses (like SARS-CoV-2) AND DNA viruses (specifically African Swine Fever Virus) to show comprehensive understanding of the project scope

5

Mention the London Centre for Nanotechnology specifically and how its interdisciplinary environment aligns with your research approach

✉️ What to Emphasize in Your Cover Letter

['Your specific experience with machine learning applications in biological/chemical contexts (not just general ML knowledge)', 'How your background prepares you for the integration of computational and experimental methods central to this project', 'Your understanding of fragment-based drug discovery and NMR spectroscopy in inhibitor identification', "Why you're particularly interested in viral RNA polymerases as targets and the broader implications for pandemic preparedness"]

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🔍 Research Before Applying

To stand out, make sure you've researched:

  • → Recent publications from both supervisors' labs (Werner Lab on RNA polymerases, Waudby Lab on NMR methods)
  • → UCL's specific facilities at the London Centre for Nanotechnology, particularly NMR and computational resources
  • → The CDT-AMR (Centre for Doctoral Training in Antimicrobial Resistance) program structure and requirements
  • → Current research on African Swine Fever Virus RNA polymerase specifically, as it's mentioned as an underexplored target

💬 Prepare for These Interview Topics

Based on this role, you may be asked about:

1 Technical questions about active learning algorithms and how they could be applied to NMR-based screening data
2 Discussion of previous experience with protein purification, recombinant expression, or structural biology techniques
3 Your understanding of RNA polymerase structure-function relationships and potential inhibitor binding sites
4 How you would approach integrating robotic automation with experimental workflows
5 Questions about specific challenges in targeting viral polymerases versus host polymerases
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⚠️ Common Mistakes to Avoid

  • Focusing only on computational OR experimental aspects without demonstrating ability to bridge both domains
  • Generic statements about machine learning without specific examples of biological/chemical applications
  • Not demonstrating awareness of the specific viral targets mentioned (RNA viruses AND African Swine Fever Virus)

📅 Application Timeline

This position is open until filled. However, we recommend applying as soon as possible as roles at mission-driven organizations tend to fill quickly.

Typical hiring timeline:

1

Application Review

1-2 weeks

2

Initial Screening

Phone call or written assessment

3

Interviews

1-2 rounds, usually virtual

✓

Offer

Congratulations!

Ready to Apply?

Good luck with your application to University College London (UCL)!

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