APPLICATION REQUIREMENTS & SELECTION PROCESS:

Please provide both research and teaching statements of up to two pages for each in addition to a full CV.
Your research statement needs to outline your plans and intentions for research activity and grant capture over the coming five years. This document will be treated in the strictest confidence and with full respect for ownership. The teaching vision should outline your areas of teaching expertise and a range of potential teaching subjects as well as course development interests. These are mandatory components of the selection process, without which we will be unable to progress your application. In your teaching vision please outline how else you would see yourself contributing to a positive and inclusive environment at Bath.
The presentation about your research will be held on Monday 27th October, Interviews will be held on Tuesday 28th October.

Join our thriving Department of Chemistry as a Lecturer in AI/ML applied to drug discovery

• You will develop an internationally leading independent research programme.
• You will teach applied AI/ML in a drug discovery context in both lectures and computational classes, more specialised units in the final year (in both departments) and contribute to our PGT course on Drug Discovery (joint with the department of Life Sciences), maintaining the University’s high standards in teaching and learning, and its inclusive and supportive learning environment.
• You will be supported to contribute at an appropriate level to the administration, leadership, and management of the Department’s activities.

At Bath we offer an exceptional environment for research teaching and learning and we wish to support you in reaching your potential for internationally leading research, in the broad field of AI/ML applied to drug discovery. We would be interested to hear from you if your research interests lie in applied AI/ML in the widest sense (a non-exhaustive list):
Generative AI for drug design and optimisation; Models to evaluate target-molecule interactions; Models to predict relevant properties of drugs; AI and ML methods to rapidly screen both drug targets and drug candidates; accelerating molecular simulation of biological systems with ML.
If you could interact with and complementing (and enhance) existing research within the department this would be advantageous.