PhD position in machine learning for scientific inference for behavioural science
We are looking for a PhD candidate (1.0 fte) who will make machine learning more scientifically useful. At the intersection of statistics, machine learning, and behavioural science, you will develop meta analysis for results from machine learning.
What you will do
ML methods provide unprecedented flexibility and powerful predictions, which are critical for modeling the complex and often high-dimensional associations underlying human behavior. However, results of ML models are more difficult to interpret than those of traditional statistical methods and uncertainty quantification is rarely provided, making it difficult to obtain generalizable scientific conclusions. We will address this challenge by developing a) methods that produce valid, generalizable and interpretable effect sizes with accurate uncertainty estimates; b) ML-based meta-analysis, in which results can be compared and combined across studies. The project is led by Dr. Marjolein Fokkema and funded by the Dutch Research Council (NWO).
Your tasks will involve:
- Developing new statistical methods and implementing these in open-source software.
- Testing the new methods through simulation studies and applying them to real-world behavioural science data.
- Publishing results in scientific journals and presenting results at (inter)national conferences.
- Collaborating with researchers from behavioural science and related fields to better understand studies and datasets the methods could be applied to, and facilitating such applications, for example through methodological or software improvements, or the writing of software documentation and tutorials.
- Taking courses and workshops tailored to your development, for example (but not limited to) those offered within the Graduate School of Social and Behavioural Sciences.
Where you will work
You will be working within the Methodology and Statistics Unit, a dynamic unit focusing on Neuroimaging Statistics, Statistical Learning and Artificial Intelligence, Applied Psychometric and Sociometric Modelling, and Responsible Research Methods. The successful candidate will have the opportunity to work with a dynamic, international team of researchers and contribute to cutting-edge research in their field. The team values scientific integrity, open science, and inclusiveness. If you are a highly motivated individual with a passion for data analysis and research, please apply with your resume and motivation letter.
What you bring
- A completed (research) master's degree in statistics, data science, psychology, or a related quantitative field.
- Strong programming skills in R, experience with data analysis and Monte Carlo simulation studies
- Strong written and spoken English, clear communication skills (both written and oral).
- A genuine interest in behavioural science, for example illustrated by relevant coursework, projects, or other academic or extracurricular activities.
In addition, the following skills are desirable (but not required):
- A background in methods for Bayesian (high-dimensional) regression, interpretable machine learning, and meta-analytic techniques, as evidenced, for example, by relevant coursework and research or thesis projects.
- Experience in the development of statistical methods and/or statistical software.
What we offer
We also offer:
- An employment contract for (38 hours per week) as a PhD candidate, initially for a period of 1 year, with the possibility of extension for 3 years after a positive evaluation. This contract falls under the CLA of Dutch Universities;
-
A salary between €3059 - €3881 gross per month, based on a full-time appointment (38 hours) (PhD student);
-
A holiday allowance (8%), an end-of-year bonus (8,3%), and an attractive pension scheme at ABP;
-
Full reimbursement of public transport commuting costs for home-to-work travel;
-
Flexible working hours: as a standard, you are entitled to a minimum of 29 leave days on the basis of a full-time working week of 38 hours; you can also save for extra leave, for example by working 40 hours a week, and in this way accrue an extra 96 leave hours, or exchange 96 leave hours for a 36-hour week.
-
Lots of options when it comes to secondary employment conditions; we can, for example, discuss options for a sabbatical or paid parental leave. Within our terms of employment individual choices model, you can exchange leave days and/or salary for benefits such as an advantageous sports subscription and bicycle scheme;
-
If your work allows it, hybrid working is possible within the Netherlands;
-
A home-working allowance (day and internet allowance) and attention for good workplaces. The University will also provide you with a laptop and a mobile telephone.
What we find important
Promoting an inclusive community is central to Leiden University’s values and vision. Leiden University aims to be an inclusive community in which all students and staff members feel valued and respected, and are able to develop to their full potential. Diversity in experiences and perspectives enriches our teaching and strengthens our research. High-quality education and research means inclusive education and research.
Want to apply or find out more?
- We believe mobility is very important. That is why we are also publishing this vacancy internally. In case of equal suitability, we will give priority to the internal candidate.
-
A pre-employment screening (references, diplomas, certificate of good conduct (VOG)) may be part of the selection procedure.
- Acquisition in response to this vacancy is not appreciated. If you nevertheless choose to send us CVs, no rights can be derived from this. #LI-Hybrid