Daniella Okyere

Please tell us about your current role and employer. 

I graduated with an MSc in Health Data Science in December 2023 and I am currently pursuing a PhD at the University. My research focuses on identifying biomarkers for hypertension using artificial intelligence and machine learning. I work within an interdisciplinary research environment that brings together data scientists, clinicians, and biomedical researchers to deepen our understanding of hypertension and contribute to data‑driven healthcare innovation.

What does a typical day in your current role look like?

A typical day involves coding and working with large datasets to uncover meaningful patterns. I also spend time reviewing scientific literature to stay current with emerging research and often focus on writing and refining my research outputs.
My days frequently include supervisory and collaborative meetings, where I discuss progress and troubleshoot challenges with colleagues. These interactions help guide my research direction and ensure alignment with the broader aims of the project.

How do you feel the learning experience on your course helped to prepare you for your career?

The programme provided an exceptional learning environment, led by passionate academics who encouraged curiosity and confidence. The combination of lectures and practical sessions was especially valuable, allowing me to apply theoretical concepts immediately and build strong technical foundations. Throughout the course, I strengthened my coding skills in languages such as R and Python, developed a solid understanding of statistical methods, and gained hands‑on experience with real‑world health datasets. The range of assignments, from individual projects to group work, helped me cultivate transferable skills including communication, critical thinking, and problem‑solving. One of the most influential aspects of the course was my thesis project. It provided early exposure to the research process and taught me how to communicate scientific findings, manage a long-term project and collaborate effectively with my supervisor, all of which continue to shape my work as a PhD student.

What were the best things about your course?

A major highlight of the course was the strong balance between lectures and practical sessions. Additionally, the course fostered an environment that encouraged collaboration and creativity. This blend of academic depth and practical application helped me develop confidence as a data scientist and equipped me for the demands of research.

What was your biggest achievement during your course?

My biggest achievement was publishing my thesis. At the beginning of the MSc, I never imagined reaching that milestone, but the support of my supervisor, Dr Animesh Acharjee, and the skills I developed throughout the programme made it possible. The process taught me resilience, and I truly enjoyed the journey.