Open Positions

NEWS: Two post-doctoral fellowships (18 months) at the University of Turin!

As part of the PRIN project “From Models to Decisions”, two post-doctoral fellowships are opening at the University of Turin in the Department of Philosophy and Education. The duration of both positions is 18 months. The research topics are "Assessing Scientific Models" and "Uncertainty in Decision-Making" and are described at the bottom of the page. Candidates need to have pursued a PhD in philosophy of science or a related philosophical subdiscipline.

Employment Terms and Conditions. The selected candidate will be appointed as a research fellow (assegnista di ricerca) for a period of 18 months. The fellowship (“assegno”) is exempt from regular income tax under Italian legislation; only some social security contributions apply. The gross amount of the fellowship is 24,400 €; this translates to a monthly net salary of ca. 1,800 €. (Turin is a city with low living costs.) Sufficient travel funds are present in the project. The successful candidate should collaborate with other project members on a regular basis and contribute to the research activities of the Center for Logic, Language and Cognition (LLC), to which he or she will be affiliated. There are no teaching obligations.

Language. Knowledge of Italian at the time of application is not required. It is expected to learn Italian to the degree that one can deal with elementary bureaucratic matters.

Application and Deadlines. The deadline for applications is on April 22, 2021, at 13:00 Italian Time (UTC+2).  Applications must be submitted through the PICA system at https://pica.cineca.it/unito/assegni-di-ricerca-unito-2021-ii/. Applicants can apply for one of the two positions or for both of them (in which case they need to file two separate applications). Any application should contain, as part of the CV file, a short description of the proposed research (ca. 500 words) in line with the research topics highlighted below.

Selection Process. Interviews are scheduled for mid-May (remotely) and information about the outcome will be sent as soon as possible afterwards. The default starting date is 1 July or 1 September 2021.

For further questions please contact the project leader, Prof. Jan Sprenger, at jan.sprenger@unito.it

Research profiles of the positions

Position I. Assessing Scientific Models. This postdoctoral fellowship is part of the work package No. 2, "Assessing Scientific Models", in the PRIN project "From Models to Decisions". The project conducts a systematic analysis of the interplay between the epistemic and the practical dimension of scientific modeling. This specific work package is focused on the probabilistic assessment of scientific models.

The successful candidate will preferentially work on one or more of the following topics:
---generalizations of Bayesian updating;
---integrating Bayesian reasoning into alternative model evaluation criteria, e.g., truthlikeness;
---interpreting Bayesian models under conditions of substantial model uncertainty;
---a synthesis of Bayesian model assessment with other forms of statistical and confirmatory reasoning;
---the role of practical goals in Bayesian model-building and Bayesian inference;
---case studies of one of the above problems in the special sciences.

Position II: Uncertainty in Decision-Making. This postdoctoral fellowship is part of the work package No. 3, "Integrating Model Uncertainty and Expert Judgment in Decision-Making", in the PRIN project "From Models to Decisions". The project conducts a systematic analysis of the interplay between the epistemic and the practical dimension of scientific modeling. This specific work package is focused on how uncertainty about scientific models affects the decisions that scientists and policy-makers make.

The successful candidate will preferentially work on one or more of the following topics:
---the nexus between model-based estimates and practical decisions;
---the role of experts in scientific decision-making;
---how uncertainty about a scientific model affects decision-making;
---the development of strategies for dealing with this uncertainty;
---case studies of one of the above topics in the special sciences.