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The application deadline for admittance and matriculation in the following fall term is December 1st. Candidates who are short-listed for potential admission will be contacted about interviews and subsequent steps before mid-January.
Applicants must obtain a master's degree before they are admitted to the doctoral program.
It is strongly recommended that applicants who did not receive their master's degree from a Swiss university take the GRE (Graduate Record Exam) General Test. Applications without GRE test results will be reviewed, but not submitting GRE test results will be considered a drawback and must be offset by very strong academic credentials (e.g., high grade point average, relevant research experience).
Proficiency in English is required. No specific test is required, but applicants who have taken the TOEFL (Test of English as a Foreign Language) are encouraged to provide a copy of the official test results.
Note: Degrees from Master of Advanced Studies programs (e.g. MAS, EMBA, MBA, etc.) do not qualify for acceptance to our program.
Students are expected to devote themselves full-time to our PhD program.
You will be informed about the outcome of your application within six weeks after the deadline.
Applicants are only admitted to the Doctoral Program in Neuroeconomics if funding for their studies has been secured either by one of the chairs at the Department of Economics or by the applicant him/herself. If you have already received funding for your doctoral studies, please remember to include a copy of the funding approval in your application package.
Courses begin in September.
Initial applications should be submitted (in electronic form only; one single PDF file per applicant) to the Doctoral Program Coordinator (dpneuro@econ.uzh.ch). These must include:
The following are brief descriptions of a few potential projects open to new PhD students. Please note that funding is not tied to specific projects, and we encourage PhD students to work closely with our faculty to develop their own tailored research projects.
Stick to the current course of action and exploit the rewards it provides or switch and explore other, potentially more rewarding options? This exploration-exploitation dilemma is one of the most basic dilemmas facing decision makers and its optimal solution requires a balance between the two strategies. However, multiple studies reported suboptimality in this type of decision-making in both healthy and clinical populations. In our project, we aim to elucidate the neural basis of behavioral flexibility and decision optimality and provide a knowledge basis for disorders affecting these functions. To this end, we plan to combine multiple techniques such as functional and structural magnetic resonance imaging and eye-tracking. Moreover, we plan to use pharmacological intervention to investigate a causal relationship between neurotransmitter systems in the brain, brain activity in predefined regions of interest and behavioral differences in resolving exploration-exploitation dilemma.
We typically do not consume goods in isolation but in combination (for example, coffee with cake, tea with milk, bread with butter). Sometimes, the value of the combination is higher than the value of the two goods consumed in isolation. In this project, we aim to understand the neural mechanisms underlying valuation when goods are combined and how this valuation is affected by internal (biological) or external (context) factors. In particular, we focus on how memory and learning influence the (conditional) valuation of combined goods, both in the lab and in real-life consumption behavior. Applicants who have experience with advanced fMRI methods (e.g. multi-voxel pattern analysis or representational similarity analysis) and/or analyzing purchasing data (e.g. Nielsen) are particularly encouraged to apply.
Dyscalculia – a persistent deficit in the acquisition of numerical and arithmetical skills – is a neurodevelopmental disorder that majorly affects the life success and well-being of the affected individuals. Even though this disorder is common, we know very little about its neural origins and exact behavioral consequences. In this project, we will investigate the precision with which the brains of adolescents diagnosed with dyscalculia can represent abstract magnitude information, and how this in turn affects their risk-taking in financial decisions with real-life consequences. To this end, the project will employ a combination of novel psychophysical and choice tasks, behavioral modelling, and sophisticated fMRI approaches (population receptive field modelling). Taken together, the project will not only elucidate brain mechanisms contributing to risk-taking behavior, but will also provide important knowledge about disrupted brain mechanisms in dyscalculia and how these may contribute to everyday behavioral problems.
Attention and working memory constraints are critical limiting factors in many aspects of human behavior, including decision making. The aim of this project is to determine if an individual’s working memory capacity together with specific features of the choice problem compound the influence of visual inattention on choice accuracy. Empirical research has shown that visual fixations (a proxy for attention) play a causal role in determining the outcome of choices. This is true for both perceptual and value-based choices. Sequential sampling models of decision making often quantify the influence of attention as a relative discount rate on all items that are not fixated relative to the one that is. Although most studies of the role of visual attention on choice have focused on group-level estimates, recent work has shown that there are substantial differences in the size of this fixation-dependent discount rate across people, and that individuals who discount unattended items more steeply make more suboptimal choices. However, the underlying reasons why fixation-dependent discount rates differ between individuals are unknown. This project will test the hypothesis that the influence of attention on choices is proportional to working memory capacity and load. Applicants who have experience with eye-tracking methods and Bayesian computational modeling are particularly encouraged to apply.
Functional magnetic resonance imaging (fMRI) is a key methodological tool in neuroeconomics and many other areas of psychology and biological sciences. This project aims to determine how improvements to fMRI hardware/software, experimental design, and statistical analysis can be used to produce or extract more information (and/or more reliable information) from resting-state, traditional task, and naturalistic viewing experiments. Thus, the project will involve close collaborations between experts in both the biological and physical sciences. Applicants with strong mathematical and computational modeling skills are encouraged to apply. Previous experience with multi-voxel pattern analyses of fMRI is a strong plus.
