PhD and MScR supervisors
We strongly encourage you to get in touch with a potential supervisor before making an application.
If you are interested in studying for a PhD or MScR with us, please find out more about our supervisors, below.
Click on the name of an academic to link out to their profile on Edinburgh Research Explorer to find out more about their research interests and publications.
|Area of research interest
Infectious disease epidemiology (particularly HIV, RSV, impact of vaccines on AMR) using mathematical modelling and phylogenetic analysis.
|Miguel O. Bernabeu
Microvascular Biomechanics and Mechanobiology: interested in gaining mechanistic insight into the process of vascular remodelling during angiogenesis and diabetic retinopathy; mixed experimental and computational methods; developing computational models for the study of microvascular Biomechanics and Mechanobiology.
|Palliative care, anticipatory/ advance care planning, health professional communication, complex health care interventions, mixed method research
provision of cancer screening in UK and international health contexts; the interface of primary care and cancer screening programmes; understanding factors influencing timely diagnosis of symptomatic cancer; inequalities in cancer care; mixed-methods health services research
|International Child Health, Global Health Epidemiology, and colorectal cancer epidemiology (including genetic and omic epidemiology); childhood respiratory infections including RSV; estimation of global and regional burden of disease.
|Epidemiology research and health policy evaluation in China, with a special focus on selected non-communicable diseases.
Ethical, social and policy dimensions of emerging biomedical and health technologies, including genetic and genomic technologies; stem cells and regenerative medicine; reproductive technologies; new modes of health research including experimental medicine and data science; animal ethics and conservation bioethics.
|Medical and family sociology including the social aspects of genetics and stem cell research, as well as research on families, health and illness across the lifecourse; lay perspectives, understandings and experience, as well as lay/professional relationships particularly in relation to public involvement and engagement in science and medicine; qualitative methods within the interpretivist tradition.
|health informatics, qualitative methods, innovation
|AI and data-driven innovation in healthcare. Adoption (procurement, implementation, evaluation, use) of AI in healthcare. Effects of AI technology adoption for clinicians, clinical practice, healthcare practices and their outcomes. AI technology procurement strategy and processes. Implications of AI tools for clinical/healthcare pathways and workflows. Implications of AI for clinical work and expertise. Ethical aspects of AI. AI governance (responsibility, trustworthiness). Healthcare AI validation and audit.
Molecular epidemiology of cancer, with emphasis on breast and bladder cancers, with particular interest on tissue biomarkers and their association with risk, prognosis and treatment outcomes. Population-based e-health records data analysis with tissue repositories and imaging data. Genetic susceptibility studies and global health research.
|Health systems and Health Workforce Development in low and middle income countries; development and integration of Palliative Care services into national health systems in low income countries; inequalities in health, barriers to service access and utilisation of services in low income settings; rRole of e and mhealth in facilitating access and improving health outcomes; Global Burden of Non Communicable diseases; Male Circumcision rituals and traditions; HIV/AIDS in Sub Saharan Africa; Spirituality and health and the role of Faith Based communities in supporting health care.
|pragmatic emergency care trials and clinical decision/risk prediction tools especially in cardiovascular emergencies and sepsis. Health intervention opportunities in emergency care. Emergency care systems.
|Primary care, multimorbidity, polypharmacy, quality and safety of healthcare particularly (but not exclusively) in relation to prescribing, mixed methods research, analysis of large quantitative datasets, epidemiology, complex intervention development and evaluation, applied health services research
Health Economics; Cancer Informatics
|Child and family health: Including parenting in the context of illness; children’s experiences of health and illness; negotiation of care. Sexual and reproductive health: including young people’s sexual health services; experiences of abortion.
|Global surgery and data science, including clinical trials, machine learning, natural language processing, mobile data collection platforms, wearables, automated data processing and display, decision modelling/Bayesian statistics, administrative data analysis, and patient reported outcomes.
|Quantitative projects in the area of chronic disease epidemiology, specifically stroke, heart disease and diabetes and multimorbidity (particularly mental health and physical health co-morbidity). Health inequalities and gender differences in disease occurrence and outcome. Systematic review methodology.
|Qualitative methods, diabetes self-management (patient and health professionals’ perspectives and experiences), clinical trial participation, barriers and facilitators to diet, physical activity and medication adherence, patient experience of chronic illness.
|Methodology relating to the conduct of randomised clinical trials, particularly on data sharing and anonymisation, central statistical monitoring, and other practical issues.
|Research and audit related to acute illness with a focus on critical care; improving underpinning methodology in this research area; research methods include epidemiology, health services research and methods using linked datasets.
|Applications of machine learning methods in medical informatics research, with special interest in the analysis of communication and interaction in medical settings such as multidisciplinary team meetings, doctor-patient consultations and telemedicine, and methods for inference in high-dimensional data sets.
Medical education; statistics education; quality of statistical reporting; specific learning difficulties (SpLDs); applications of statistics in clinical research; use of mixed methods (a combination of qualitative and quantitative research techniques) in educational and clinical research; systematic reviews, including meta-analyses; psychometrics; health measurement scales; standard setting of educational assessments; reliability estimation for educational assessment scores; use of educational technology; the philosophy of mathematics and statistics, including concepts of infinity; the logic of statistical hypothesis testing
|Statistical genetics; molecular epidemiology; diabetes; disease stratification.
|Multiple sclerosis and vitamin D; diabetes epidemiology in sub-Saharan Africa; epidemiology of non-communicable diseases.
|Life after stroke, Frailty, Shared decision making, Palliative care, Exercise for chronic disease, Systematic reviews, Large RCTs, Complex intervention design
|Felicity Vidya Mehendale
|Application of Artificial Intelligence (AI) to improve global medical care. Machine learning (ML) algorithms for outcome evaluation, as diagnostic aids and to predict long term outcomes, with a focus on cleft lip and palate (speech, facial appearance, surgical safety). Epidemiology of congenital anomalies, particularly orofacial clefts. Addressing barriers to early diagnosis, referral and intervention for newborns with birth conditions in low resource settings, through m-health and training, to develop standardisation of newborn examination and congenital anomaly registries. Telemedicine to improve access to care, follow up and outcome data collection. Hypochlorous acid (HOCl) as a sustainable, safe surgical disinfectant.
|Mixed-methods research, Multimorbidity, Mental Health, Inequalities, Inverse care law ,Empathy, Mindfulness, social prescribing
|Epidemiology based projects in (paediatric) infectious diseases, refugee health, gender inequities in child health.
|Exploration and evaluation of eHealth interventions, including organisational and social influences on implementation and clinical and psychosocial impacts. Systematic review and policy analysis of eHealth risks and benefits. Evaluating complex interventions. Linking policy and research. Consumer and patient engagement. Therapy adherence in chronic disease.
|The sociology of biomedicine and biomedical technologies; the sociology of psychiatry, psychology and the mental health professions.
|My key area of interest is the delivery of care for people with common respiratory disease. Specific topics are supported self-management for asthma (and other long-term conditions), supportive and palliative care for people with severe chronic obstructive pulmonary disease (COPD), telehealth for asthma and COPD. Methodological interests are mixed method evaluations (including trials, process evaluations, qualitative studies) and particularly pragmatic and implementation studies.
|Molecular epidemiology of vascular disease, vascular and non-vascular complications of diabetes and age-related cognitive impairment; evidence-based healthcare for peripheral vascular disease.
|Global health epidemiology and policy.
|Data Ethics; responsible regulation, governance, ethical, legal and social aspects of data driven innovation, trust and autonomous systems, regulation of healthcare and health research
Application of data-driven technology in healthcare: this includes signal processing to extract information from time-series data using wearables, machine learning to find patterns in data as well as data fusion, development of intelligent algorithms for clinical decision support, and digital health solutions including telemonitoring solutions as well as applications running on a smartphone. Application areas are broad but at the moment, I have particular interest in chronic disease management especially respiratory illnesses such as asthma and COPD.
|Epidemiology and clinical management of asthma and allergic disorders; Exploiting innovations in eHealth to promote patient and population health and to increase the efficiency of care; Burden, causes and consequences of medical error and development of strategies and interventions to enhance patient safety; Reducing health inequalities.
|Statistical Genetics, Quantitative Genetics, Biostatistics, Genetic Epidemiology, Statistical Modeling of High-Throughput Molecular Data
|Care homes (residents - especially transitions from acute care, and staff), Cognitive ageing, delirium and dementia (especially vascular), Frailty, Innovation and technology for older people, Systematic reviews (especially observational studies), Data linkage, Epidemiology.
|epidemiology based projects focusing on respiratory infections, global burden of disease estimate.
Machine and statistical learning methods applied to genetic and biomarker datasets linked to health outcomes; genetic epidemiology; disease stratification; prediction of drug response
Global health governance, institutions, financing. Mixed-methods (quantitative & qualitative).
Epidemiology; Treatment optimisation; Treatment adherence; Pharmacoepidemiology; Basic sciences-epidemiology interface; Quantitative research methods; Tuberculosis; Epstein Barr Virus; Other infectious diseases; Chronic conditions
|Epidemiology and clinical studies in maternal and newborn health; Medicine use in pregnancy; Developmental origins of health and wellbeing; Risk prediction and communication of risk in pregnancy; Efficient clinical trials and use of routine healthcare data.
|Cancer epidemiology, especially colorectal cancer; Field synopses of genetic association studies; Epidemiology of glycans in health and disease; International Health.
|Time-series analysis, signal processing, statistical machine learning, speech analysis, wearables. Designing decision support tools through data analytics and algorithm development, assisting remote diagnosis and telemonitoring. Applications primarily in mental/neurological disorders.
|Methodology relating to the design of randomised clinical trials, including: adaptive designs; cluster randomised trials; and statistical methods for evaluating surrogate outcomes. Projects applying statistical methods to data from randomised controlled trials.
|Cancer, 'medically unexplained symptoms', and evidence-based primary care; role of primary care in screening, early diagnosis and management.
|Genetics of complex disease: genetic architecture, gene discovery, rare variants, isolated populations, whole genome sequence, homozygosity, Y chromosome, mtDNA, proteomics.
|Epidemiology of diabetes and other chronic diseases; Use of routine data for research.
|Infectious disease epidemiology.
|Clinical data science, especially text mining, machine learning, knowledge graph techniques on healthcare data
Sexual and reproductive health, HIV, pharmaceuticals for prevention, emerging health technologies, gender, sexuality, LGBT health, migration, inequalities, health literacy, health activism, qualitative research methods, participatory research, knowledge exchange
Academic staff interested in supervising PhD students should contact the Postgraduate Administrator, Sebastien Georges: firstname.lastname@example.org
If you are an academic listed above, and would like to amend any details, please contact email@example.com.