Research Fellow & Biostatistician - Large-Scale Health Data in Manchester

Research Fellow & Biostatistician - Large-Scale Health Data in Manchester

Manchester Full-Time 30000 - 40000 Β£ / year (est.) No working from home possible
UNSW

At a Glance

  • Tasks: Analyse large health datasets and collaborate on impactful research projects.
  • Company: UNSW, a leading institution in health research and innovation.
  • Benefits: Flexible working hours, competitive salary, and opportunities for professional growth.
  • Other info: Join a dynamic team dedicated to advancing health outcomes.
  • Why this job: Make a difference in public health through data-driven research.
  • Qualifications: PhD in relevant field and experience with statistical software and health data.

The predicted salary is between 30000 - 40000 Β£ per year.

UNSW is hiring a full-time Research Fellow (Biostatistician) in Manchester. This role focuses on statistical analysis of health datasets in collaboration with investigators, covering areas such as HIV prevention and HPV vaccination.

The ideal candidate will have a PhD, proficiency in statistical software, and experience with health data.

The position offers a flexible working arrangement, competitive salary, and professional development opportunities.

Research Fellow & Biostatistician - Large-Scale Health Data in Manchester employer: UNSW

UNSW is an exceptional employer, offering a dynamic work environment in Manchester where innovation meets collaboration. With a strong emphasis on professional development and flexible working arrangements, employees are empowered to grow their skills while contributing to impactful health research. The competitive salary and supportive culture make UNSW a rewarding place for those passionate about making a difference in public health.

UNSW

Contact Details:

UNSW Recruitment Team

We think you need these skills to ace Research Fellow & Biostatistician - Large-Scale Health Data in Manchester

Statistical Analysis
Proficiency in Statistical Software
Experience with Health Data
Collaboration Skills
PhD in Relevant Field
Data Interpretation
Research Methodology