Postdoctoral Research Associate in Systems Medicine

at  Kings College London

Job id: 097325. Salary: £44,105 per annum, including London Weighting Allowance.
Posted: 18 October 2024. Closing date: 27 October 2024.
Business unit: Faculty of Life Sciences & Medicine. Department: Department of Inflammation Biology.
Contact details: Cheng Zhang. cheng.5.zhang@kcl.ac.uk
Location: Denmark Hill Campus. Category: Research.
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About Us
King’s College London is one of the world’s leading research universities, renowned for its excellence in education, groundbreaking research, and innovation. Our Faculty of Life Sciences & Medicine (FoLSM) is dedicated to pushing the frontiers of medical science to improve healthcare outcomes. Within FoLSM, the School of Immunology & Microbial Sciences (SIMS) plays a key role in research and education, with a focus on understanding the mechanisms of disease and developing new therapies.
This role is located within the prestigious Roger Williams Institute of Liver Studies, where our researchers are at the forefront of liver disease research. As part of this vibrant academic environment, you will join the Zhang group, an innovative research team at the intersection of systems medicine, bioinformatics, and liver disease. Based at the James Black Center, Denmark Hill campus, our team works on understanding and modeling metabolic and inflammatory processes that drive liver disease progression. We are dedicated to advancing scientific knowledge and translating our research into real-world medical solutions, offering a dynamic and collaborative setting for cutting-edge research.
About the role
This role offers a unique opportunity to contribute to innovative research at the forefront of systems medicine, focusing on the progression of Metabolic Associated Steatotic Liver Disease (MASLD). The successful candidate will work within a multidisciplinary team to unravel the metabolic drivers of MASLD through cutting-edge spatial multi-omics and computational metabolic modeling.
The role involves developing and implementing computational methods to integrate genome-scale metabolic models (GEMs) with single-cell and spatial transcriptomics data. Using advanced techniques such as MALDI-MSI metabolic profiling and enzyme-constrained GEMs, the candidate will generate region-specific models to predict metabolic fluxes associated with liver disease. This research will provide key insights into the metabolic alterations driving MASLD progression, with the ultimate goal of contributing to the development of novel diagnostic and therapeutic strategies.
The post is based at the James Black Center, Denmark Hill campus, and the candidate will report directly to Dr. Cheng Zhang. The successful candidate will collaborate closely with clinicians, computational biologists, and experimentalists, ensuring that computational models are seamlessly integrated with experimental data. Responsibilities also include the supervision of junior researchers and the preparation of high-impact research publications.
This role is ideal for individuals with expertise in systems biology, bioinformatics, and multi-omics data analysis, who are eager to make significant contributions to the field of liver disease research. This is a fixed-term position for two years, with a potential start date in December 2024, providing an exciting opportunity to be part of a dynamic and forward-thinking research group.
This is a full time post (35 Hours per week), and you will be offered a fixed term contract until 30 January 2026.
About You
To be successful in this role, we are looking for candidates to have the following skills and experience:

Essential criteria

• PhD qualified in relevant subject area *
• Strong programming skills with proficiency in Python, R, and tools relevant to multi-omics data analysis (e.g., CellRanger, GECKO, tINIT)
• Demonstrated ability to work independently, manage time effectively, and meet competing deadlines in a dynamic research environment
• Experience in analyzing large-scale multi-omics datasets, including transcriptomics, proteomics, and metabolomics, using advanced statistical and computational methods
• Expertise in genome-scale metabolic models (GEMs) and familiarity with flux balance analysis or other metabolic flux modeling approaches
• Ability to communicate effectively within a multi-disciplinary team and produce high-quality verbal and written reports and publications
• Please note that this is a PhD level role but candidates who have submitted their thesis and are awaiting award of their PhDs will be considered. In these circumstances the appointment will be made at Grade 5, spine point 30 with the title of Research Assistant. Upon confirmation of the award of the PhD, the job title will become Research Associate and the salary will increase to Grade 6.

Desirable criteria

• Knowledge of liver disease, cancer and/or metabolism
• Strong problem-solving skills and the ability to develop novel computational methods for data integration and analysis
• Experience with machine learning approaches for biological data modeling and predictive analytics

Downloading a copy of our Job Description
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