The Department of Methodology and Statistics at Utrecht University has a job opening for a PhD candidate for the development of novel statistical algorithms to treat missing data in large, longitudinal datasets.
In this project, candidates will work under the supervision of a team of three experts in missing data analysis, statistical computing, and longitudinal modeling to extend the abovementioned work to accommodate longitudinal data (e.g., by incorporating multilevel PCA methods). Although these new methods will suit diverse contexts, they will specifically target applications in developmental science. The methods you develop, therefore, will be designed to support valid estimation and inference in popular models of growth and temporal association (e.g., latent growth curves, [random intercept] cross-lagged panel models).
They will use Monte Carlo simulation studies to compare the performance of the new methods to the current state-of-the-art in missing data treatment for longitudinal/nested data. As these simulation studies will necessarily entail a high computational demand, they will offer an excellent opportunity to learn and practice high-performance computing techniques.
In addition to the statistical computing that will be woven throughout their methodological research, candidates will also have the opportunity for hands-on software development experience.
Duration: 4 years
Salary
In accordance with the collective labor agreement for Dutch Universities, they offer:
- a working week of 38 hours and a gross monthly salary between €2,770 and €3,539 in the case of full-time;
- 8% holiday pay and 8.3% year-end bonus;
- a pension scheme, partially paid parental leave and flexible terms of employment based on the CAO NU.
Job Requirements
For the Imputation Routines for Longitudinal Data Job, they seek an enthusiastic colleague who meets the following criteria:
- holds (or nearly holds) a Master’s degree in Methodology and Statistics or a related field;
- has strong programming skills in R, some experience with statistical computing, and an interest in high-performance computing;
- has an interest in open-source software development and will commit to implementing and distributing any new methods as open-source software;
- is a motivated, communicative, and collaborative team member who can work harmoniously in small teams;
- has an interest in open science and will commit to following open-science principles;
- has excellent verbal and written communication skills in English;
- can time-manage in the context of long-term projects to complete tasks independently while keeping team members apprised of progress.
Application Process
Applications in one pdf should include:
- Letter of motivation;
- Curriculum vitae.
To apply for the Developing Scalable Multiple Imputation Routines for Longitudinal Data (PhD), click here.
Deadline: June 02, 2024.
For more information on Developing Scalable Multiple Imputation Routines for Longitudinal Data (PhD), visit the official site.
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