Research Associate in Health Data Science

Salary: £33,966 to £44,263 per annum

Join Newcastle University, a top-tier workplace known for its excellent benefits. We provide a comprehensive holiday package with opportunities to purchase additional days, excellent pension schemes, and numerous health and wellbeing initiatives to support our staff.

Closing Date: 23 June 2024

The Role

We are currently inviting applications for the position of Research Associate within the Data Science & AI Programme at the NIHR Innovation Observatory (IO), based at Newcastle University. The IO, supported by £27M in NIHR funding, serves as a cohesive hub that integrates the expertise of horizon scanning analysts, evidence synthesis researchers, and data scientists to monitor and report on health innovation.

In this role, your primary focus will be on researching and developing advanced data-driven AI tools. You will play a critical role in enhancing our in-house developed OpenScan platform by leveraging generative AI and large language models (LLMs) to process and analyze diverse health data. This role demands a combination of cutting-edge research and practical application to ensure the development of robust, efficient, and impactful tools.

This position is available on a fixed-term basis until 31 March 2026.

For informal inquiries, please contact Dr. Christopher Marshall at .

To support your career development, Newcastle University has developed three levels of research role profiles detailing the competences and responsibilities for each level as well as the qualifications and experiences required for entry.

Key Accountabilities

• Research and develop AI-based data science tools, focusing on generative AI and LLMs, to support the IO’s research activities.
• Enhance the data ingestion pipeline and application layers of OpenScan, improving data crawling, extraction, and analysis capabilities.
• Manage and execute research projects within agreed timelines, ensuring that project milestones are met to a high standard.
• Oversee the collection, processing, and management of structured and unstructured health data, ensuring data integrity and accessibility.
• Collaborate with cross-functional teams across the IO, providing the necessary tools and support to other researchers.
• Maintain clear documentation and communicate technical progress effectively to both technical and non-technical colleagues and stakeholders.
• Develop and deliver training sessions on AI tools and methods, enhancing the skill set of colleagues and fostering a collaborative learning environment.
• Mentor junior researchers and provide guidance on best research practices in AI and data science.
• Prepare and publish research articles, and present findings at national and international conferences and seminars.
• Build and nurture relationships with internal and external stakeholders, participating in networks to facilitate knowledge exchange and collaboration.
• Represent the IO at external meetings and seminars, promoting our work.

Essential Knowledge, Skills and Experience

• PhD or equivalent professional expertise in a relevant field such as data science, computer science, or software engineering.
• Proven experience with AI methods, including machine learning, data mining, and natural language processing.
• Strong proficiency in Python programming.
• Strong background in data management, curation, linkage, and analysis of large heterogeneous datasets.
• A record of publishing in peer-reviewed journals and presenting at academic conferences.
• Excellent analytical, problem-solving, and critical thinking skills.

Desirable Skills

• Familiarity with healthcare regulatory and market access processes.

Attributes and Behaviour

• Ability to work independently and collaboratively within a team.
• Strong organizational, communication, and interpersonal skills.
• High attention to detail and commitment to accuracy.
• Self-motivated, proactive, and enthusiastic about research.
• Ability to build effective relationships with diverse stakeholders.
• Commitment to high-quality research and continuous improvement.

Qualifications

• PhD in Computer Science, Data Science, or a related discipline.