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- Tasks: Join a team to develop global population estimates using advanced statistical methods.
- Company: Be part of a leading research initiative at the University of Southampton.
- Benefits: Gain experience in a collaborative environment with opportunities for professional growth.
- Why this job: Contribute to impactful research that shapes demographic understanding and policy.
- Qualifications: PhD in a relevant field or nearing completion, with strong statistical skills required.
- Other info: Work closely with experts and enhance your programming skills in R or Python.
The predicted salary is between 36000 - 60000 £ per year.
To be successful in this role you will have, or will be close to completing, a PhD (or have equivalent professional qualifications and experience) with a strong statistical or mathematical component, such as in statistics, demography, economics, geography, or mathematics. Essential attributes for the role are: experience in statistical modelling; proficiency in the use of R, Python or other equivalent programming language; the ability to plan and organise work independently and as part of a team; and the ability to write research presentations and papers. Additionally, knowledge of demographic projection methods, knowledge of Bayesian statistical methods, and/or experience of working with geospatial data would be an advantage.
Applications for Research Fellow positions will be considered from candidates who are working towards or nearing completion of a relevant PhD qualification. The title of Research Fellow will be applied upon successful completion of the PhD. Prior to the qualification being awarded the title of Senior Research Assistant will be given.
The project is led by Dr Laurence Hawker and Prof. Andy Tatem and aims to produce high spatial resolution (100m grid cell) global age/sex-structured population estimates for multiple socio-economic scenarios. This project extends previous work conducted by the WorldPop and University of Bristol groups by incorporating spatially varying patterns between covariates and population size, as well as by quantifying uncertainty around estimates.
This post sits within a FuturePop work package focused on the production of subnational population projections by administrative geography. Estimates at high spatial resolution are produced by disaggregation of such estimates and projections, and thus the post forms a key part of the workflow in this area. In particular, the post-holder will develop probabilistic methodology to produce estimates and projections of the global population by subnational areas.
The work package is led by Dr Jason Hilton, Dr Laurence Hawker and Prof. Andy Tatem, and the research position will be based in the Department of Social Statistics and Demography, but the post holder will also need to develop strong working relationships with colleagues in the School of Geography and Environmental Sciences and at the University of Bristol.
Informal enquiries may be addressed to Dr Jason Hilton, email: J.D.Hilton@soton.ac.uk.
Job offer Research Fellow in Demographic Modelling/Senior Research Fellow in Population Forecasting employer: WELLCOME TRUST
Contact Detail:
WELLCOME TRUST Recruiting Team
J.D.Hilton@soton.ac.uk
StudySmarter Expert Advice 🤫
We think this is how you could land Job offer Research Fellow in Demographic Modelling/Senior Research Fellow in Population Forecasting
✨Tip Number 1
Make sure to highlight your experience with statistical modelling and programming languages like R or Python in your conversations. This will show that you have the technical skills needed for the role.
✨Tip Number 2
Familiarize yourself with demographic projection methods and Bayesian statistical methods. Being able to discuss these topics confidently can set you apart during interviews.
✨Tip Number 3
Network with current or former colleagues from the University of Bristol or those involved in similar projects. They might provide insights or even refer you to the position.
✨Tip Number 4
Prepare to discuss how you can contribute to the project’s goals, especially regarding high spatial resolution population estimates. Showing your understanding of the project's objectives will demonstrate your enthusiasm and fit for the role.
We think you need these skills to ace Job offer Research Fellow in Demographic Modelling/Senior Research Fellow in Population Forecasting
Some tips for your application 🫡
Highlight Relevant Qualifications: Make sure to clearly outline your PhD progress or equivalent qualifications in your CV. Emphasize any strong statistical or mathematical components in your education and experience.
Showcase Technical Skills: Detail your proficiency in R, Python, or other programming languages in your application. Provide specific examples of how you've used these skills in previous projects or research.
Demonstrate Research Experience: Include information about your experience in statistical modeling and any relevant research presentations or papers you have written. This will showcase your ability to contribute to the project effectively.
Tailor Your Application: Customize your cover letter to reflect your understanding of the project led by Dr. Laurence Hawker and Prof. Andy Tatem. Mention your interest in demographic projection methods and any experience with geospatial data.
How to prepare for a job interview at WELLCOME TRUST
✨Showcase Your Statistical Skills
Be prepared to discuss your experience with statistical modelling in detail. Highlight specific projects where you utilized R, Python, or other programming languages, and be ready to explain the methodologies you employed.
✨Demonstrate Independent and Team Work
Share examples of how you've successfully planned and organized work both independently and as part of a team. This will show your versatility and ability to collaborate effectively with others.
✨Familiarize Yourself with Demographic Projection Methods
Brush up on demographic projection methods and Bayesian statistical techniques. Being able to discuss these topics confidently will demonstrate your expertise and readiness for the role.
✨Prepare for Geospatial Data Discussions
If you have experience working with geospatial data, be sure to prepare examples of how you've applied this knowledge in past projects. This will be a valuable asset in the context of the position.
