Contract: Full-Time (35 hours per week), Open Ended
Role Description
Heriot-Watt University invites applications for an Assistant or Associate Professor in Statistical Data Science, with a specialisation in health and medical applications. This role is pivotal in advancing the University’s research and teaching capabilities in statistical data science, with a particular focus on applied statistics and statistical machine learning within healthcare.
The successful candidate will have the opportunity to shape the curriculum, drive impactful research, and contribute to public health policy and outcomes through innovative data science applications.
Key Duties and Responsibilities
Research Leadership
- Lead and contribute to large-scale research projects focused on applying statistical data science to health and medical data, addressing critical challenges in healthcare.
- Secure research funding from research councils, industry partners, and health-related organisations, building an independent funding portfolio.
- Build and sustain collaborations with interdisciplinary teams across departments such as Biomedical Engineering, to drive impactful research that influences healthcare policies and public health outcomes.
- Disseminate research findings through high-impact journal publications, conferences, and public engagement activities.
Teaching and Curriculum Development
- Develop and deliver new postgraduate taught programmes related to statistical data science, targeting numerate students from diverse fields, such as the health sciences, biology, psychology, and urban planning.
- Innovate curriculum content in statistical data science, focusing on health data applications, machine learning, epidemiology, and geospatial data science.
- Supervise graduate and postgraduate students, supporting their research projects and career development, with a specific focus on health-related data science.
Interdisciplinary and Industry Collaboration
- Establish and maintain partnerships with healthcare organisations and industry stakeholders, advancing the University’s contributions to healthcare innovation and public health improvements.
Public Engagement and Community Impact
- Participate in public outreach initiatives, sharing research insights that contribute to the societal understanding of health data science.
- Actively engage in professional organisations and community health projects, fostering public engagement and enhancing the University’s visibility in health and care innovation.
Education, Qualifications and Experience
Essential
- PhD in statistical data science, applied statistics, epidemiology, or a closely related field.
- Strong research background in statistical data science with applications to health or medical data, evidenced by a track record of high-impact publications.
- Experience in securing research funding, ideally with a focus on health-related data science.
- Demonstrable teaching experience, with a commitment to developing and delivering data science programmes tailored to interdisciplinary and healthcare applications.
- Proven ability to collaborate effectively with diverse stakeholders, including academic colleagues, industry partners, and public health organisations.
- Excellent communication skills, with the ability to engage students, colleagues, and the wider community.
For all criteria, further details and how to apply, please click on the ‘Apply’ button above.
Heriot-Watt University is committed to securing equality of opportunity in employment and to the creation of an environment in which individuals are selected, trained, promoted, appraised and otherwise treated on the sole basis of their relevant merits and abilities. Equality and diversity are all about maximising potential and creating a culture of inclusion for all.
Heriot-Watt University values diversity across our university community and welcomes applications from all sectors of society, particularly from underrepresented groups. For more information, please see our website https://www.hw.ac.uk/uk/services/equality-diversity.htm and our award-winning work in Disability Inclusive Science Careers https://disc.hw.ac.uk/.