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Project description
We are looking for two talented and ambitious PhD candidates in methodology and statistics as part of the NWO-funded VICI project “Towards personalized multi-disciplinary treatment plans: The next generation of structural equation modelling tools” (SEM2.0).
Background
Non-observable constructs such as personality, intelligence, and well-being are at the core of research on human behaviour and cognition. Latent variable methods (e.g., factor analysis, structural equation modelling) are therefore an indispensable tool for research in the social and behavioural sciences. These methods are known to work well when the number of parameters to estimate is relatively small compared to the sample size: This is when the number of variables is small and the models are not too complex. However, two aspects of modern research practices challenge these conditions and cause existing methods to fall short: (1) a trend to use intensive collections of data (“Big Data”) and (2) the call for person-centric models.
The SEM2.0 project develops the next generation of structural equation models, suitable for working with highly complex data problems. It builds on a strong modelling framework that explicitly includes the latent variables and avoids the ill-conditioned problem of inverting covariance matrices. Furthermore, alternating optimization and parallel computing methods will be used to obtain powerful and scalable algorithms that have good convergence properties. This makes them effective for the analysis of (big) data. By adding regularizing constraints the method will account for simple structure, the presence of joint and specific latent variables in multidomain data, alignment in multigroup and longitudinal data, and the need for personalization of the measurement and/or structural model. Regularization is a powerful tool to add structure to the data analysis and to avoid overfitting in highly complex models. In collaboration with health- and well-being researchers, large collections of data resulting from two empirical studies will be analyzed to develop methods and software that can and will be used by many researchers.
The first PhD project focuses on developing and validating the next generation of structural equation models for binary data and fits in the framework of item factor analysis and multidimensional IRT models; the second PhD project focuses on the development and validation of SEM methods for out-of-sample prediction.
Your position
The PhD position is integral to a broader research initiative, which includes other PhD students and staff members. Regular meetings with the supervisor will be scheduled to review and discuss the project's advancement. The department fosters an open working culture, emphasizing mutual respect and appreciation among its members.
Your responsibilities
Your background
We are looking for a strong PhD candidate with a relevant (Research) Master’s degree with a background in applied/mathematical statistics, machine learning, sociometrics, econometrics, or the like, and a strong interest in computational statistics. Candidates with a social science degree with very strong quantitative skills can also apply. The degree should be completed or almost completed. Other requirements include:
Increasing your value
With us, you will find everything you need to maximize your potential and development. We offer excellent facilities and support for research, education, and making societal impact. In all three of these areas, we “recognize and reward” you in line with national university aspirations. With great opportunities such as collaborating in an academic collaborative center, or participating in our Connected Leading program. We attach great importance to team spirit and have a clear, shared vision of (personal) leadership (Connected Leading). Read more about careers at Tilburg University and personal development here.
Your valuable contribution will be rewarded with attractive benefits and sufficient attention to work-life balance. Our offer includes:
In addition to your monthly salary, you will receive 41 vacation days (for a 40-hour work week), a holiday allowance (8%), and a year-end bonus (8.3%). We reimburse the full cost of sustainable commuting: walking, cycling, or public transportation. We have a moving expenses scheme that makes it attractive to live close to the university. You will be enrolled in the ABP pension fund through us. Our Options Model allows you to choose from a variety of facilities at a tax advantage. You can work in a hybrid manner: on campus and, for a reimbursement, from home. Researchers from outside the Netherlands may qualify for a tax-free allowance of 30% of their taxable salary if they meet the relevant conditions. The university applies for this allowance on their behalf.
Your work environment
You will work in a pleasant working environment; a green campus with plenty of facilities. At a leading, entrepreneurial, and innovative university in the humanities and social sciences. The university employs 2,400 staff members and hosts 20,000 students of some 100 different nationalities. For nearly a century, this organization has worked together with a tradition aimed at contributing to society. We strive to be a community where differences in age, gender, orientation, and cultural and religious backgrounds are valued, with equal opportunities for colleagues and students and where, moreover, all decisions take into account the importance of preserving the Earth for future generations.
Read more about the university here.
Tilburg School of Social and Behavioral Sciences (TSB) is one of the five faculties of Tilburg University. The teaching and research of the Tilburg School of Social and Behavioral Sciences are organized around the themes of “Adaptive societies, organizations, and workers”, “Healthy life span”, and “Personalized prevention and care”. The School’s inspiring working environment challenges its workers to realize their ambitions, involvement and cooperation are essential to achieve this.
Tilburg School of Social and Behavioral Sciences | Tilburg University
For more information about the department of Methodology & Statistics, see: https://www.tilburguniversity.edu/about/schools/socialsciences/organization/departments/methodology-statistics.
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