Research Assistant for the EmergAI project Full-time

Research Assistant for the EmergAI Project

Are you interested in evaluating how AI can improve the diagnosis of acute myocardial infarction – and whether it is cost-effective? Are you looking for an employer that invests in sustainable employeeship and offers safe, favourable working conditions? We welcome you to apply for a Research Assistant position at Uppsala University.

The Department of Medical Sciences is a large clinical institution with more than 250 employees and over 900 additional coworkers connected via the Uppsala University Hospital. The Department of Medical Sciences has a broad research profile with strong research groups in a number of different areas. The research carried out at the department is performed in close connection with the clinical activities at the Uppsala University Hospital, which includes both basic studies on the causes of a variety of illnesses and the development and evaluation of improved diagnostics and new treatment methods.

Within the EmergAI project at the Department of Medical Sciences, a register-based cost-effectiveness analysis (CEA) of AI-based ECG interpretation for detection of occlusion myocardial infarction (OMI) in the emergency department is being conducted. An AI model developed at Uppsala University has demonstrated high discriminative performance for OMI, offering potential to reduce both missed diagnoses and unnecessary angiographies. No published health economic evaluations of AI-ECG for acute myocardial infarction diagnostics currently exist; this is the first planned study of its kind.

The study is individual-level and register-based, with linkage to national quality registers and administrative registers as well as regional cost data. The analysis is conducted from healthcare and societal perspectives in accordance with CHEERS 2022 and the guidelines of the Dental and Pharmaceutical Benefits Agency (TLV), using methods for censored cost data (IPCW/Zhao-Tian), multiple imputation (MICE), bootstrap, probabilistic sensitivity analysis (PSA), and expected value of perfect information (EVPI).

Duties include:

• Finalising and refining the project plan and methodological specification in collaboration with the project team
• Conducting a systematic literature review of published CEAs of AI-based diagnostics
• Building the health economic analysis model in R: an 8-cell classification matrix for AI predictions and physician decisions, cost calculations using DRG-weighted unit costs, QALY calculations based on EQ-5D data from SEPHIA, handling of censored costs, and uncertainty analysis (DSA, PSA, EVPI)
• Conducting subgroup analyses (educational level, age, sex)
• Contributing to manuscript preparation for scientific publication and to dissemination for general audiences

We are looking for a candidate with a master's degree in health economics, public health, epidemiology, statistics, or a related field. You have documented experience of health economic evaluations (CEA/CUA), are well versed in relevant methodological frameworks (CHEERS, TLV guidelines), and are independently proficient in statistical programming in R. You have specific competence in multiple imputation (MICE), bootstrap methods, and probabilistic sensitivity analysis, and you are able to work independently and in a structured manner in an academic research environment.

Experience of Markov modelling and methods for censored cost data is advantageous, as is prior work with Swedish national registers (the National Patient Register, the Cause of Death Register, LISA, SWEDEHEART). Experience of health economic analyses using EQ-5D/QALYs as outcome measures is also meritorious, as is knowledge of EVPI methodology and the health economics of AI-based diagnostic interventions. Experience of manuscript preparation for scientific publication is additionally advantageous.

The employment is a temporary position, 6 months. Scope of employment 100 %. Starting date as agreed. Placement: Uppsala.

For further information about the position, please contact: Johan Sundström, Professor, johan.sundstrom@uu.se, +46 70 422 52 20

Please submit your application by 19 June 2026, UFV-PA 2026/1966.