We are seeking a highly motivated and talented individual to join our team spanning between LSBU and GSK as a PhD student in the field of model-based meta-analysis for drug development. The successful candidate will work on developing cutting edge methods to merge individual and aggregated data into drug-disease model(s): using both Bayesian approaches and Machine Learning (ML).
Responsibilities:
- Conduct comprehensive literature reviews and collect relevant data for model-based meta-analysis
- Develop and implement statistical and ML methodologies, in the context of drug-disease modelling, able to utilize a combination of summary and individual data
- Apply and assess the developed methods on real case examples
- Simulate and re-estimate realistic scenarios with varying degree of non-linearity of the model, covariate dimensionality and correlation to assess the developed methodologies
- Collaborate with other team members to ensure successful completion of the research projects
- Present research findings at conferences and in scientific publications
- Complete all required coursework and exams necessary to obtain a PhD degree
Entry requirements:
- Master’s degree in statistics, biostatistics, biomedical engineering, pharmacometrics, or a related field with at least a 2:1 (or equivalent)
- If English is not your first language, a IELTS score of at least 7.0 at postgraduate level
Desired skills
- Strong quantitative skills and experience with statistical modelling, and parametric models
- Familiarity with model-based meta-analysis and its applications in drug-disease modelling
- Proficiency in programming languages such as Python or Matlab, R, and in statistical packages such as RStan/PyStan
- Excellent written and verbal communication skills
- Ability to work collaboratively in a team environment
- Strong problem-solving skills and attention to detail
Benefits:
- Fully funded scholarship
- Opportunity to work with a highly collaborative and interdisciplinary team of researchers across academia and industry
- Access to state-of-the-art resources and equipment for research
- Opportunities for professional development and training
If you are a highly motivated individual with a passion for using quantitative methods to improve drug development decisions, we encourage you to apply for this exciting PhD position in model-based meta-analysis.
For informal inquiry, please contact:
Enrico Grisan: [Email Address Removed]
Monica Simeoni: [Email Address Removed]
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