Funded PhD studentship: Effects of electromagnetic fields including light exposure from mobile phone technology on health in the COSMOS cohort

Primary supervisor: Professor Mireille Toledano

Overview: Mobile phones and other digital technologies play a ubiquitous role in the lives of adolescents in today’s digital era. This age group may be particularly sensitive to the effects of radiofrequency electromagnetic fields (RF-EMF) emitted from mobile phones and other wireless technologies, as the brain is still developing. The Study of Cognition, Adolescents, and Mobile Phones (SCAMP), launched in 2014, has been following up participants for over 10 years. SCAMP is the largest research project of its kind in the world, exploring how mobile phones and wireless technologies may affect cognition (i.e., how people think, make decisions and process information), behaviours, and physical and mental health of young people. Over the next few years, the SCAMP study will continue to follow more than 10,000 young people across Greater London to explore how young people use their mobile phones in everyday life and understand whether mobile phone use, including exposure to RF-EMF and screen light, has any long-term effects on their brain development, mental health, and wellbeing. Research findings will inform public health policy in relation to the use of non-ionising radiation technologies in young people.

This is an environmental exposure assessment and epidemiology PhD project.  This PhD project will include the following elements.

Data collection and integration:

• Support and contribute to follow-up data collection from the SCAMP cohort for the study of RF-EMF and possible health effects. This may include design, development, and testing of questionnaires, preparation of study materials, applying for ethical approvals, and communication with cohort members.

Exposure assessment:

• Estimate robust metrics for young people’s use of digital technologies, reflecting the complex nature of usage (intersection of duration, behaviour, platforms), with an emphasis on advancing exposure assessment approaches/methodology.
• Estimate cumulative and integrated RF-EMF exposure metrics.
• Explore possibilities for exposure assessment of 5G technology use/exposure in the SCAMP cohort.

Epidemiological analyses:

• Conduct statistical analyses exploring the complex longitudinal relationships between digital behaviours and RF-EMF exposure with cognitive function and mental health in SCAMP, whilst exploring the influence of factors such as sleep, physical activity, genetic susceptibility, and pubertal hormones, on these relationships.

Public and community involvement, engagement and participation:

• Engage with the public (e.g. via the Young People’s Advisory Group (YPAG)) to support the communication of research outputs and ensure their relevance to cohort members and the wider public.

Dissemination:

• The PhD student will be expected to write up findings for publication in peer-review journals, to present findings at national and international meetings, and to write up findings in a style appropriate for lay audiences for dissemination via website, media and newsletters to cohort members.

Who the PhD student will work / liaise with: supervisors, SCAMP data manager, SCAMP team members and collaborators, investigators under HPRU in Radiation Threats and Hazards, and NHS data providers.

About the NIHR HPRU RTH

The NIHR HPRU in Radiation Threats and Hazards is led by Professor Paul Elliott and Professor Liz Ainsbury. Our vision is to improve evidence and capacity for effective protection of the population from radiation risks, reduce health inequalities from such risks, and influence public health policy in this important area. We aim to advance knowledge on the distribution, determinants, mechanisms and pathways linking radiation exposures to health effects and strengthen response to ionising radiation accidents.

Successful PhD candidates will be supported by a bespoke training programme to ensure that they are equipped with the appropriate skills and experience to become first-class researchers.

Eligibility Criteria

Essential:

• Candidates should hold, or achieve by the start of the programme, a Master’s degree in addition to a Bachelor’s degree with a UK First- or Upper Second-Class honours grade or equivalent in a relevant life science or quantitative science subject.
• Strong background in statistics and quantitative data analysis and familiarity with statistical/computational tools (e.g., R, Python, Stata).
• Candidates must meet Imperial College’s English language requirements (Higher level) unless exempt.

Desirable:

• Experience in machine learning, public health, or epidemiological research.
• Experience working with or communicating with young people.

Funding and Start Dates

• Home tuition fees covered plus a tax-free annual stipend starting at around £22,780+ based on UKRI 2026/27 UK PhD stipend.

• Start date: 1 October 2026.
• Open only to applicants eligible for Home fee status.

Research Environment

The student will be based in the HPRU team within Imperial’s School of Public Health, located at the White City Campus. The Centre provides an interdisciplinary environment and opportunities for collaboration across Imperial and partner institutions.

You will also collaborate with our partner institutions UK Health Security Agency (UKHSA), King’s College London, Institute of Cancer Research and MRC Toxicology Unit at the University of Cambridge.

Supervisors: Professor Paul Elliott, Professor Mireille Toledano, Dr Rachel Smith, Dr Azadeh Peyman

Overview: The COSMOS study was established to address key questions about the potential long-term health effects of mobile phone use and other sources of radiofrequency electromagnetic fields (RF-EMF). By using a prospective cohort design and objective data sources, COSMOS overcomes many of the limitations and biases that affected earlier research in this field. The study follows over 300,000 adult mobile phone users, including 100,000 in the UK, and will analyse outcomes such as rare cancers (e.g. acoustic neuroma), cardiovascular disease, and neurodegenerative conditions in relation to well-characterised mobile phone use prior to disease onset. The cohort has approximately 15 years of follow-up to date. As new technologies emerge, we are incorporating analyses of 5G usage and exposure, including the potential impacts of 5G base stations on sleep quality and wellbeing. We will also explore effects of non-natural light exposure, such as screen use, on health. A new follow-up questionnaire is in development to examine 5G technologies, sleep, and environmental light exposure.  We expect the findings from this PhD project to feed directly into the advisory and regulatory framework nationally and internationally for the safe use and implementation of mobile phone technologies.
 
This is an environmental exposure assessment and epidemiology PhD project.  This PhD project will involve a combination of the following elements. Some are essential, but there is some scope to tailor these in places to the student’s skill set/interests.

Data collection and integration:

• Support and contribute to engagement with, and follow-up data collection from, the UK COSMOS cohort (questionnaires, operator data, routine health data) for the study of RF-EMF and possible health effects. This may include design, development, and testing of questionnaires, preparation of study materials, applying for ethical approvals, and communication with cohort members.

Exposure assessment:

• Conduct exposure assessment for 5G technology use/exposure in the UK COSMOS cohort, e.g. combining of questionnaire data and 5G coverage maps.
• Estimate robust mobile phone use and cumulative and integrated RF-EMF exposure metrics for epidemiological analyses.
• Conduct statistical analysis of changes in mobile phone use over time in the UK COSMOS cohort, utilising questionnaire and operator data.

Epidemiological analyses:

• Conduct statistical analyses of the relationship between mobile phone use, RF-EMF exposure, and specific health outcomes (cancers, adverse birth outcomes, neurodegenerative diseases, cognitive performance) [N.B. exact health outcomes might vary, depending on follow-up time accrued and statistical power, particularly for cancers and neurodegenerative diseases].
• Conduct statistical analyses of the relationship between light at night (from smartphones) and health outcomes in UK COSMOS.
• Conduct statistical analyses of the relationship between smartphone and social media use and mental health outcomes in UK COSMOS.

Public and community involvement, engagement and participation:

• Engage with the public (via forums such as the Public and Community Oversight Group (PCOG)) to support the communication of research outputs and ensure their relevance to cohort members and the wider public.

Dissemination:

• The PhD student will be expected to write up findings for publication in peer-review journals, to present findings at national and international meetings, and to write up findings in a style appropriate for lay audiences for dissemination via website, media and newsletters to cohort members.

Who the PhD student will work / liaise with: supervisors, COSMOS data manager, partners in the wider COSMOS Consortium, HPRU in Radiation Threats and Hazards, UK mobile operators, NHS data providers.

About the NIHR HPRU RTH

The NIHR HPRU in Radiation Threats and Hazards is led by Professor Paul Elliott and Professor Liz Ainsbury. Our vision is to improve evidence and capacity for effective protection of the population from radiation risks, reduce health inequalities from such risks, and influence public health policy in this important area. We aim to advance knowledge on the distribution, determinants, mechanisms and pathways linking radiation exposures to health effects and strengthen response to ionising radiation accidents.

Successful PhD candidates will be supported by a bespoke training programme to ensure that they are equipped with the appropriate skills and experience to become first-class researchers.

Eligibility Criteria

Essential:

• Candidates should hold, or achieve by the start of the programme, a Master’s degree in addition to a Bachelor’s degree with a UK First- or Upper Second-Class honours grade or equivalent in a relevant life science or quantitative science subject.
• Strong background in statistics and quantitative data analysis and familiarity with statistical/computational tools (e.g., R, Python, Stata).
• Candidates must meet Imperial College’s English language requirements (Higher level) unless exempt.

Desirable:

• Experience in machine learning, public health, or epidemiological research.

Funding and Start Dates

• Home tuition fees covered plus a tax-free annual stipend starting at around £22,780+ based on UKRI 2026/27 UK PhD stipend.
• Start date: 1 October 2026.
• Open only to applicants eligible for Home fee status.

Research Environment

The student will be based in the HPRU team within Imperial’s School of Public Health, located at the White City Campus. The Unit provides an interdisciplinary environment and opportunities for collaboration across Imperial and partner institutions.

You will also collaborate with our partner institutions UK Health Security Agency (UKHSA), King’s College London, Institute of Cancer Research and MRC Toxicology Unit at the University of Cambridge.