Complex scenarios create deep uncertainty about the consequences of our actions. Outcomes are hard to predict and quantify, and uncertainty can also affect which options exist and how valuable they are for us or for others.

The PhD candidate is expected to investigate reasoning and decision-making under uncertainty from both theoretical and applied perspectives.

The theoretical component should aim to draw on analytic (including formal) epistemology, philosophy of science, and accounts of rationality and decision-making, aiming to refine our understanding of uncertainty and assess the limits of mathematical modelling under such conditions.

The applied component should focus on real-world case studies. Projects exploring emerging technologies, including (but not limited to) social robots as embodied systems for human-machine interaction and AI as decision-support tools in uncertain contexts, are particularly encouraged. The PHD candidate is also expected to contribute to and lead experimental activities using tools such as VR technologies, simulations, and AI. 

Aviation is a priority application area, given its reliance on automation, heuristics, predictive models, and human factors, as well as its relevance to safety systems and risk mitigation. Other application domains will also be considered.

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Candidates should have training or familiarity in at least one field relevant to the project. Strength in areas central to “Severe Uncertainty: Decisions, Evidence, and Probability” is an advantage, including analytic epistemology (formal or social), philosophy of science, reasoning, and decision-making. Background in logic or mathematics is useful. Applicants should be open to multidisciplinary work and applying philosophical methods to underexplored sustainability-related domains. Familiarity or experience with specific application areas (e.g., aviation) is beneficial.

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The team specializes in epistemology, philosophy of mathematics and logic, and theories of risk, uncertainty, and decision-making, alongside philosophy of mind, affectivity, and technology. It includes professors, researchers, and postdocs, and organizes seminars, workshops, and masterclasses while supporting international collaborations. Members contribute to competitive research projects and multidisciplinary MA and PhD programs. The PhD position is 50% funded by the project “Severe Uncertainty: Decisions, Evidence, and Probability (DeEP)” (FIS-2023-01696), led by Luca Zanetti - CUP I53C25000600001. 

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