MRC Postdoctoral Research Scientist in Steroids & Metabolism LMS 2596
Salary: £42,694 plus London allowances £5,560 per annum
Fixed Term 3-years | Full time | Closing Date: 27 July 2026
Research Programme
The main research focus of the Steroids and Metabolism group led by Prof Wiebke Arlt is the investigation of steroid biosynthesis and metabolism and their impact on human health and disease, with a specific focus on the sex-specific link between androgen biosynthesis and metabolism and metabolic dysfunction. We employ human-based ex vivo and in vivo physiology and experimental medicine approaches as well as steroid metabolome profiling by mass spectrometry in conjunction with exploration of the data space by statistical and machine learning methods. We develop new diagnostic and prognostic tools and precision medicine approaches with a focus on endocrine and metabolic women’s health.
Purpose of Post
To investigate the relationship between the steroid metabolome, the global untargeted metabolome and clinical phenotype parameters in large cohorts of women affected by polyendocrine metabolic ovarian syndrome and endometriosis, respectively.
You will be expected to carry out research within the focus area of the Steroids and Metabolism Group; undertake project management and be involved in the supervision of MRes and PhD students in the group. You need to be willing and able to communicate complex computational issues in the transdisciplinary space, which includes explaining computational method details and analysis results to biological researchers. In addition, you will be expected to present research at conferences, submit publications to refereed journals and to help attract external research funding
Main duties / key responsibilities:
Working relationships:
The post-holder will report directly to the head of the group, Professor Wiebke Arlt.
Additional information:
This post is an MRC Postdoctoral Scientist, created to support post-doctoral training and help develop and establish successful research scientists in their chosen field. During the fellowship tenure we are committed to provide mentorship for career development and enhancement of communication and engagement skills, in addition to scientific progression.
Corporate/Local responsibilities & requirements
The job holder must at all times carry out their responsibilities with due regard to the MRC’s:
- Code of Conduct
- Equality and Diversity policy
- Health and Safety policy
Data Protection and Security policy
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Job descriptions should be reviewed on a regular basis and at the annual appraisal. Any changes should be made and agreed between the post holder and their manager.
The above lists are not exhaustive and the job holder is required to undertake such duties as may reasonably be requested within the scope of the post. All employees are required to act professionally, co-operatively and flexibly in line with the requirements of the post and the MRC.
Person requirements
Education / Qualifications / Training required (will be assessed from the application):
Essential:
PhD degree in Computer Science or a related quantitative discipline with substantial training and expertise in statistical and machine learning methods
Desirable:
Undergraduate degree in Biology or Biochemistry
Previous work experience required (will be assessed from the application and at the interview):
Essential:
Experience in statistical and machine learning analysis of complex data
Desirable:
- Experience of working in the interdisciplinary context in collaboration with biological and quantitative scientists
Experience in translational and entrepreneurial activities
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Personal skills/behaviours/qualities (will be assessed at the interview):
Essential:
- Evidence of organisational ability
- Good written and verbal communication skills and the ability to work effectively with researchers ranging from postgraduate students to professorial level
Ability to work both independently and as part of a team
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Additional information:
A highly committed individual with proactive and flexible attitude to work.
The ability and willingness to learn new concepts and technologies rapidly whilst collaborating with different scientific disciplines.
How to apply:
Applicants should submit one CV, a brief cover letter describing how the candidate meets the person specifications and the motivation for the post, and the names and contact details of two scientific references.
Please note that applications may be reviewed by both LMS and Imperial staff
