Careers
Graduates from the Applied Statistical Modelling & Health Informatics (ASMHI) MSc at King’s College London go on to make an impact across research, healthcare, and industry. Equipped with skills in AI, statistical modelling and health informatics, they work at the forefront of evidence-based health innovation; from predicting disease to improving clinical trials and digital health tools. Many of our graduates choose to pursue a career in research and academia, and many are well equipped to begin their PhD studies in a related field.
Careers Options for ASMHI Graduates
Clinical and Health Data Analysts
In organisations such as the NHS, Prostate Cancer UK, and international research units.
Medical and Applied Statisticians
In academic trials units (e.g. NPEU Clinical Trials Unit, Oxford University) and pharmaceutical or CRO settings (e.g. Medpace, IQVIA, Veramed).
AI & Machine Learning Researchers
Developing predictive models, digital biomarkers, and computational tools for mental health, precision psychiatry, and complex biomedical data.
Bioinformaticians and Genomics Researchers
Working on large-scale omics data and disease genetics (e.g. IoPPN Genomics Core Facility).
Consultants and Data Scientists
Applying quantitative methods to healthcare, policy, and life sciences (e.g. True North Partners, DWP, BioMérieux).
Public Health and Epidemiology Analysts
Contributing to international research on infectious diseases, environmental health, and health inequities.
PhD and Research Positions
In health data science, bioinformatics, precision psychiatry, neurodegeneration, and AI for healthcare (e.g. King’s College London, University of Oxford, City St George’s, LMU Munich). The department hosts a fully funded PhD programme; DRIVE-health.org.uk.
What our ASMHI Graduates do now
Phichayut Phinyo
ASMHI MSc, 2023-2024
Phichayut is an Assistant Professor in Biomedical Informatics and Clinical Epidemiology at Chiang Mai University. A clinician-scientist with over 170 publications, his work advances clinical prediction modelling, causal inference, and evidence synthesis to improve real-world patient care and health-system decision-making.
Irina Craciunescu
ASMHI MSc, 2020-2022
Irina is a Regional Market Intelligence Manager for Asia-Pacific at bioMérieux. She has a strong background as a strategic marketing consultant across ASPAC and CEE-META regions, delivering data-driven market insights using statistical modelling and health economics within the IVD and healthcare sectors.
Kamil Krakowski
(ASMHI MSc, 2020-2021)
Kamil has worked as a Computational Mental Health Researcher at the University of Pavia in Italy, studying for his PhD. For his MSc dissertation project Kamil developed and published a pioneering dynamic psychosis prediction model using natural language processing.
Ihsan Fadilah
(ASMHI PGCert, 2020-2021)
Ihsan is an Applied Statistician at the Oxford University Clinical Research Unit (OUCRU), where his research in infectious disease and health inequity has appeared in PLOS Medicine and BMJ Global Health. His statistical analyses help inform global clinical research and public-health policy.
Irina Zhang
ASMHI MSc 2021-2022
Irina is a PhD researcher at Imperial College London developing interpretable, multimodal machine-learning and foundation models for histopathology and translational biomedical research. She previously worked as an AI Scientist at Lyzeum Ltd and as an R&D Graduate Scientist in Data Science and AI at AstraZeneca.
Chris Albertyn
(ASMHI PGCert, 2021-2022)
Chris is a Translational Health Data Scientist and Programme Manager in Psychedelic-Assisted Cancer Therapy. He applies statistical modelling and informatics to mental-health and clinical data, integrating computational and clinical insights to advance evidence-based, data-driven healthcare research.
Diya Bhandari
(ASMHI MSc, 2022-2023)
Diya is a Medical Statistician at Barts Cardiovascular Clinical Trials Unit; previously at Oxford’s NPEU Clinical Trials Unit. Her MSc research explored links between air pollution and mental-health service use in young people with anxiety disorders, informing population health insights.
Changhyun Kim
ASMHI MSc 2021-2022
Changhyun is a PhD researcher at the Institute of Cancer Research, developing AI methods for early-stage lung cancer diagnosis. His MSc research applied deep-learning, multimodal speech emotion recognition, and feature fusion strategies to neuropsychological data.
Lauren White
(ASMHI MSc, 2023-2024)
Lauren is a Higher Statistical Officer at the Department for Work and Pensions (DWP) and has previously interned at thymia (a health technology company). Her dissertation project explored the role of cognition in the relationship between depression and speech.
Charithea Stylianides
ASMHI MSc, 2020-2021
Charithea is a Research Associate and Healthcare Data Scientist at the CYENS Centre of Excellence, and previously worked as a Research Engineer at the KIOS Research and Innovation Centre. She has experience developing end-to-end machine-learning models for real-time clinical prediction with large-scale health and EHR data.
Misha Ramesh
(ASMHI PGDip, 2023-2024)
Misha is a PhD Researcher at City St George’s University, using artificial intelligence to analyse eye scans and predict dementia risk. Her research, funded by the Alzheimer’s Society, combines big-data modelling with neuroscience to improve early detection of neurodegenerative disease.
Mian Haider Ali
(ASMHI MSc, 2022-2023)
Mian is a Scientific Assistant in biomedical data science at LMU Munich, applying machine learning to predict disease trajectories in inflammatory bowel disease. His work combines AI and clinical data to improve prognostic models and support precision medicine research.
Rhys Holland
ASMHI MSc, 2024-2025
Rhys is a Clinical Data Analyst at PharosAI, working in breast cancer research. During his MSc, he developed a fairness-aware neural network for personalised antidepressant prediction and contributed to large-scale clinical and population health studies using applied statistical modelling.
Harris Wong
(ASMHI MSc 2021-2022)
Harris is a Health Data Analyst at Prostate Cancer UK, using routinely collected clinical data to strengthen evidence-based care. For his MSc project, he developed a machine-learning model using Fitbit sleep data to predict depression risk from digital health metrics
Bhakti Nagpurkar
(ASMHI MSc, 2023-2024)
Bhakti is a Research Assistant in Genomics at King’s College London, providing bioinformatics support for GWAS projects. Her ASMHI dissertation investigated structural variants in Amyotrophic Lateral Sclerosis, developing computational pipelines to understand how genomic changes drive neurodegenerative disease.