Job Description

Job number

NAT01959

Faculties

Faculty of Natural Sciences

Departments

Department of Life Sciences

Salary or Salary range

48,056 - 56,345 per annum

Location/campus

South Kensington Campus - On site only

Contract type work pattern

Full time - Fixed term

Posting End Date

27 May 2025

About the role

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This is an exceptional opportunity for an ambitious Research Associate to join a team integrating AI approaches with the design and implementation of biosynthetic pathways, in the group of Prof Geoff Baldwin at the South Kensington Campus. We are using CRISPRCas tools to target specific nodes in the E. coli metabolic network to create perturbations to metabolism.



This project seeks to integrate this approach with AI approaches to interpreting data with metabolic models. The work will be done in collaboration with the group of Prof. Jean-Loup Faulon (INRAE, Paris), who has developed a neural network-based approach to genome scale metabolic models (doi: 10.1038/s41467-023-40380-0). The project also seeks to explore alternative cutting-edge AI methodologies for the analysis of experimental data with a view to implementing active learning to create a self-optimising closed-loop system. You will be highly motivated, with good teamwork skills and a knowledge of both computational and coding approaches alongside well developed laboratory skills.

What you would be doing

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You will be responsible for developing and implementing AI methods for the analysis and interpretation of experimental data. You will actively plan the computational research methodologies and the execution of experimental analysis. This will require close collaboration with experimentalists to ensure that the approaches being developed are applicable to the data streams being generated.



You will actively participate in programme and team meetings, project updates, and collaborative discussions both internally within the team and with external partners. You will be expected to present work through the writing of papers for publication and attendance and presentation at conferences.



You will provide guidance and direction to undergraduate and postgraduate students, fostering a collaborative and productive research environment.

What we are looking for

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You should hold, or ne near completion of, a PhD (or equivalent) in a physical sciences, biological sciences, computer science or engineering or a closely related discipline, or equivalent research, industrial or commercial experience You should have a high level of expertise and skills in machine learning and AI, Inductive and Abductive Logic Programming and application of AI/ML to synthetic biology. You should have knowledge of Coding skills, including Python and knowledge of logic-based programming and coding in PROLOG or Python. You will be expected to have excellent written communication skills and the ability to write clearly and succinctly for publication.

What we can offer you

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The opportunity to continue your career at a world-leading institution and be part of our mission to continue science for humanity. Grow your career: gain access to Imperial's sector-leading dedicated career support for researchers as well as opportunities for promotion and progression. Sector-leading salary and remuneration package (including 39 days off a year and generous pension schemes). Be part of a diverse, inclusive and collaborative work culture with various staff networks and resources to support your personal and professional wellbeing.

Further information

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The post is available full-time, fixed term until 13 August 2025 with possibility of extension. You will be based at the South Kensington campus of Imperial College London.



Candidates who have not yet been officially awarded their PhD will be appointed as Research Assistant.



Should you require any further details on the role please contact: Prof. Geoff Baldwin g.baldwin@imperial.ac.uk

Available documents

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Attached documents are available under links. Clicking a document link will initialize its download.

Please note that job descriptions are not exhaustive, and you may be asked to take on additional duties that align with the key responsibilities mentioned above.

We reserve the right to close the advert prior to the closing date stated should we receive a high volume of applications. It is therefore advisable that you submit your application as early as possible to avoid disappointment.



If you encounter any technical issues while applying online, please don't hesitate to email us at support.jobs@imperial.ac.uk. We're here to help.


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About Imperial

Welcome to Imperial, a global top ten university where scientific imagination leads to world-changing impact.



Join us and be part of something bigger. From global health to climate change, AI to business leadership, here at Imperial we navigate some of the world's toughest challenges. Whatever your role, your contribution will have a lasting impact.



As a member of our vibrant community of 22,000 students and 8,000 staff, you'll collaborate with passionate minds across nine London campuses and a global network.



This is your chance to help shape the future. We hope you'll join us at Imperial College London.


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Our Culture

We work towards equality of opportunity, to eliminating discrimination, and to creating an inclusive working environment for all. We encourage applications from all backgrounds, communities and industries, and are committed to employing a team that has diverse skills, experiences and abilities. You can read more about our commitment on our webpages.



Our values are at the root of everything we do and everyone in our community is expected to demonstrate respect, collaboration, excellence, integrity, and innovation.