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"PhD Studentship: Investigating the Chronobiological Drivers and Molecular Regulators at the Neuromuscular Junction during Sarcopenia."

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PhD Studentship: Investigating the Chronobiological Drivers and Molecular Regulators at the Neuromuscular Junction during Sarcopenia.

Qualification Type:PhD
Location:Manchester
Funding for:UK Students, EU Students, International Students
Funding amount:£20,780 stipend, plus £5,006 home tuition fees for the year 2025/26. Please refer to advert for further details.
Hours:Full Time
Placed On:27th November 2025
Closes:27th February 2026
Reference:SciEng-AL-2025-26-Chrono Sarc AI

Project advert

We invite applications for a fully funded, multidisciplinary doctoral project focused on understanding the mechanistic drivers of sarcopenia, the debilitating age-related loss of muscle mass and function. This research addresses a critical unmet health challenge by exploring a fundamental, underexplored mechanism: how the disruption of the body’s internal circadian clock drives progressive decline at the neuromuscular junction, the vital connection between nerve and muscle.

You will have a unique opportunity to work with a multi-disciplinary team of cell and molecular biologists, chemists and computational experts pioneering research using an advanced, optogenetically controlled human-based nerve-muscle model. Using functional, molecular and metabolomics technologies, integrated with machine learning (ML) and artificial intelligence (AI) workflows, the project aims to create a comprehensive molecular atlas and identify novel, translational biomarkers and therapeutic targets.

Project aims and objectives

The core aim of this project is to determine how age-related circadian dysregulation impacts neuromuscular function and muscle homeostasis. This will be achieved by the following objectives:

  • Establishing a co-culture system with rhythmic stimulation to model an aged phenotype, followed by mechanistic interrogation using comprehensive metabolomics, structural, and functional analyses.
  • Using machine learning and artificial intelligence systems to integrate complex datasets, identifying and validating core molecular targets.

Funding

Both home students and international students can apply. Only home tuition fees will be covered for the duration of the 3.5-year award, which is £5,006 for the year 2025/26. Eligible international students will need to make up the difference in tuition fee funding (Band 3 for the year 2025/26).

The student will receive a standard stipend payment for the duration of the award. These payments are set at a level determined by the UKRI, currently £20,780 for the academic year 2025/26.

Specific requirements of the candidate

Essential criteria:

  • A first or upper second (2:1) class honours degree in a relevant science discipline such as Biomedical Science, Cell Biology, Molecular Biology, Physiology or a related field.
  • Strong theoretical and practical knowledge of fundamental molecular and cell biology techniques, in particular mammalian cell culture.
  • Demonstrable curiosity and enthusiasm for interdisciplinary research.
  • Excellent written and verbal communication skills.
  • Ability to work independently, manage time effectively, and collaborate as part of a team.

Desirable criteria:

  • Knowledge of the molecular basis of ageing, muscle physiology, or the circadian clock.
  • Experience or strong interest in data science, machine learning, or bioinformatics.
  • Exposure to high throughput ‘omics’ techniques, such as metabolomics.

How to apply

Interested applicants should contact Dr Adam Lightfoot for an informal discussion.

To apply you will need to complete the online application form for a full time PhD in Biological Science.

Please complete the Doctoral Project Applicant Form, and include your CV and a covering letter to demonstrate how your skills and experience map to the aims and objectives of the project, the area of research and why you see this area as being of importance and interest.

Please upload these documents in the supporting documents section of the University’s Admissions Portal.

Expected start date: Oct 2026.

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