Horizon Europe - Marie Skłodowska-Curie Actions Postdoctoral Fellowships 2025
The MSCA scheme
The Marie Skłodowska-Curie Actions (MSCA) scheme aims to support researchers’ careers and foster excellence in research.
The Fellowships aim to enhance the potential of researchers holding a PhD and who wish to acquire new skills through advanced training, international, interdisciplinary and inter-sectoral mobility.
Fellowships will be offered to excellent researchers of any nationality undertaking international mobility either to or between the EU Member States or Horizon Europe Associated Countries, as well as to associated Third Countries.
The standard duration of these fellowships must be between 12 and 24 months.
Details about the scheme are available on the Funding and Tenders Portal.
The call is expected to open on 8th May 2025 and the indicative deadline of the call is 10 September 2025.
MSCA at Bocconi:
Bocconi welcomes expressions of interest by postdoctoral candidates who wish to apply for the MSCA Postdoctoral Fellowship to be hosted at our university.
The application period for this year is closed.
Applications received via email will not be considered.
The application of eligible candidates[1] will be sent to the selected supervisors for their assessment.
Supervisors will select one candidate per project.
What we offer
Selected applicants will be offered the opportunity to undertake a proposal writing training session that will be held online on the 15th and 16th May 2025.
Additionally, Bocconi will also provide a limited number of travel grants to cover funding for travel and accommodation expenses to allow the researchers to spend a few days at Bocconi.
This will allow the researchers to benefit from insights from previous MSCA grantees, meet with their supervisors, visit the Bocconi campus and get feedback on their proposals from the Bocconi Grants Office staff.
[1] Applicants must have a PhD degree at the time of the deadline for applications (10.09.2025). Those who have successfully defended their doctoral thesis but who have not yet formally been awarded the doctoral degree will also be considered eligible to apply. Applicants must also have a maximum of 8 years’ experience in research, from the date of the award of their PhD degree, years of experience outside research and career breaks will not count towards the above maximum
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You can contact grants.office@unibocconi.it.com for any questions on the program.
Please check the available supervisors per department from the list below:
| Supervisor | Title of the project | Description | Research interests |
|---|---|---|---|
| Andrea Celli | Online learning and algorithmic game theory | The research project broadly focuses on topics at the intersection of algorithmic game theory and online learning. Possible directions include designing online learning algorithms for settings with complex feedback and simple state representations, as well as investigating the computation of generalized equilibrium concepts and associated decentralized dynamics. | algorithmic game theory, online learning, equilibrium computation |
| Carlo Lucibello | Statistical Physics | This project advances generative diffusion models by merging statistical physics with machine learning. It tackles key challenges like computational cost, lack of theory, and limitations in discrete data generation. Using methods like the replica technique and energy-based models, it studies generation quality, guidance, and memorization. A focus on discrete diffusion enables fast, interpretable generation, with applications in protein sequence modeling. Hybrid models will combine neural networks and structured physics-inspired designs. The project aims to boost both theoretical understanding and practical impact in generative AI. |
statistical physics, machine learning, spin glass theory |
| Debora Nozza | User-centered NLP | My research interests are centered around Natural Language Processing (NLP), with a particular focus on detecting and mitigating hate speech and algorithmic bias in social media data, especially in multilingual contexts. I am also deeply interest by how and why individuals engage with large language models (LLMs) in their daily lives, and how we can enhance these experiences, particularly for vulnerable populations. |
Natural Language Processing, Artificial Intelligence, Human-Computer Interaction, Decision-Making, Algorithmic Bias |
| Supervisor | Title of the project | Description | Research interests |
|---|---|---|---|
| Emanuele Borgonovo | Variable Importance for Explanable Artificial Intelligence | Variable importance measures play a central role in explainable artificial intelligence. However, their calculation is challenging. On the one hand, the designs need to keep computational burden under control. On the other hand, the approaches need to use new points that lie close to the original points to avoid model extrapolation. Furthermore, a multiplicity of models can perform equally well on a given dataset. In this project, we investigate new tools that can provide analysts with reliable importance indications in the light of the above-mentioned challenges. Specifically, we study the utilization of methods based on: a) the theory of optimal transport, with focus on the sliced Wasserstein distance; b) permutations, with focus on generalizing the theoretical basis of the recently introduced GDMR approach. | Machine Learning, Sensitivity Analysis, Variable Importance, Explainable Artificial Intelligence |
| Luca Braghieri | The economics of the media (with a particular focus on social media) | Various projects on the effects of social media on politics, mental health, etc. | Behavioral Economics, Political Economy, Media Economics, Theory |
| Elia Bruè | Optimal Transport, Ricci Curvature, and Applications | Over the past decade, optimal transport tools have proven powerful in studying spaces with Ricci curvature lower bounds, providing a synthetic approach akin to that used in Alexandrov space theory. This project targets long-standing conjectures connecting Ricci curvature bounds to geometric and topological constraints, focusing on collapsing phenomena, Lie group isometry actions, and low-dimensional rigidities. Additionally, I aim to explore the role of Ricci curvature and related tools in data analysis. |
Ricci Curvature, Non-smooth Geometry, Optimal Transport, PDE of fluid dynamics |
| Antonio De Rosa | Measure theoretic solutions of geometric problems in the calculus of variations | Several problems in the calculus of variations can be tackled by means of geometric measure theory. Solutions to geometric variational problems can be often easily found in appropriate weak measure theoretic classes. However, these measure theoretic relaxations of the original geometric problems pose the question of whether weak solutions are (almost) classical solutions. The project aims to study structural properties of measure theoretic solutions of several geometric variational problems, including (but not limited to) the classical Plateau problem, the isoperimetric problem, the min-max theory and the optimal branched transport. |
Geometric Analysis, Partial Differential Equations, Geometric Measure Theory, Calculus of Variations, Optimal Transport |
| Tangren Feng | Designing Simple Mechanisms in Complex Environments | This project investigates dominant-strategy mechanisms across a wide range of interdependent-value environments—including voting, auctions, bilateral trade, and public goods provision. What does “dominant-strategy mechanism” mean in these contexts? Do any nontrivial dominant-strategy mechanisms exist? If so, what are their defining characteristics, and what implications do they have for mechanism design? | Mechanism Design, Information Economics, Game Theory, Social Choice |
| Hugo Lavenant | Curves and maps valued in the space of probability distributions | Variational models involving curves and maps valued in the space of probability distributions are of great importance to analyze measure-valued data and can also be used as a tool to convexify problem of calculus of variations. The project aims at understanding which type of functionals one should define on the space of measure-valued maps (such as generalizations of the action, of the Dirichlet energy, and their entropic counterpart), how to discretize them, and how one can minimize the discretized counterpart in an efficient way. These questions have a strong connection with optimal transport and its geometry. |
Optimal transport, calculus of variations, convex analysis, convex optimization |
| Antonio Lijoi | New Bayesian approaches for learning distributional features and causal structures | The most popular Bayesian nonparametric models for exchangeable (or homogeneous) data are typically formulated as transformations of discrete random measures. However, in many applications, data are influenced by covariates that introduce heterogeneity. Recent research on discrete random probability measures and their associated random partitions has primarily focused on cases where covariates take on a finite number of values, assuming partial exchangeability as the most suitable probabilistic symmetry. This project builds on that research direction by extending the framework to more general covariates that can take values in arbitrary spaces. The research has two main objectives. First, we aim to develop new Bayesian testing procedures for comparing distributions associated with different covariate values. Second, we seek to establish an innovative framework for causal inference within the potential outcomes approach, where random probability measures are indexed by both the treatment and individual-specific covariate values. |
Bayesian Nonparametrics; Completely random measures; Predictive inference; Probabilistic symmetries; Survival analysis |
| Igor Pruenster | Bayesian Biodiversity Assessment Across Populations | Estimating the number of species in a population is a classical problem, extensively studied in the frequentist literature. A promising Bayesian approach, under exchangeability, combines a mixture of symmetric Dirichlet distributions with a penalization term to account for unbalanced species frequencies. This project aims to extend the method to multiple samples, as typically encountered when species data are collected across different sites, replacing exchangeability with the more flexible notion of partial exchangeability. The approach will leverage recent advances in the theory of multivariate species sampling processes to estimate both the number of species unique to each sample and those shared across samples. This will enable the identification of populations with higher species richness and the development of novel, principled biodiversity measures. | Bayesian Nonparametrics; Random Measures; Species Sampling; Mixture models; Predictive inference |
| Giuseppe Savaré | Evolution of measures | The project aims to study general classes of evolution of positive measures (also including the unbalanced case), for which the Minimizing/JKO method is no longer available, but which are nevertheless expected to have good stability properties with respect to the initial data. The correct formulation of the implicit Euler method in these cases as well as the study of its convergence to a continuous semigroup are among the main goals of the project. For further references: https://gsavare.github.io |
Optimal Transport; Gradient flows; Calculus of Variations; Geometric Analysis |
| Supervisor | Title of the project | Description | Research interests |
| Michele Fioretti | Firms' social impact | India has recently introduced a CSR tax. How does it impact both society and firms? This project aims to examine the effects of corporate social responsibility (CSR) and its regulation on society, as well as how these impacts, in turn, influence firms. By combining data analysis and modeling, the project integrates empirical industrial organization techniques with corporate finance to address key issues such as firms' strategies, productivity, markups, misallocation, and broader societal consequences. | Empirical industrial organization, ESG, corporate finance, trade |
| Massimiliano Marcellino | Functional data analysis | Combining micro and macro data is relevant to get a proper econometric model to address a set of relevant questions (e.g. distributional effects of economic policy). Functional data analysis provides a proper statistical tool, yet not so explored in empirical macro. | Time series econometrics, Bayesian econometrics, Machine learning, Empirical macro, Forecasting |
| Mara Squicciarini | Religion, Human Capital, and Innovation in a Historical Perspective | Empirical research on the relationship between religion, human capital, and innovation. Historical focus on 19th-century France and US. | Economic History, Political Economy |
| Supervisor | Title of the project | Description | Research interests |
| Elena Carletti |
Project 1: Supervision with style
Project 2: Runs in modern banking
Project 3: The political economy of banking deregulation |
Project 1: An important question is the extent to which the implementation of banking regulation through supervisory oversight has a role per se in guaranteeing financial stability. Exploiting a unique and novel dataset, the project investigates whether and how supervisory intensity and individual supervisors’ characteristics matter for the effectiveness of supervision.
Project 2: The project aims at building a new framework to study why banks offer demandable debt, even if it creates run risk. Based on some stylized facts, it departs from the standard assumptions of competitive deposit market, risk averse investors and fully leveraged banks. The results will advance our knowledge on the role of capital for financial fragility, monetary policy transmission and central bank credibility.
Project 3: The link between crises and deregulation raises the question whether banks influence regulation. The project studies this question around the passage of the Economic Growth, Regulatory Relief, and Consumer Protection Act (EGRRCPA) in 2018. The goal is to better understand banks’ influence on politicians and the channels through which this occurs. |
Financial stability, financial crises, corporate governance, central banking, sovereign debt market |
| Filippo De Marco | Credit Markets and Monetary Policy | Empirical projects studying the impact of monetary policy and inflation in credit markets using bank and firm-level data | Financial Intermediation, Monetary Economics |
| Supervisor | Title of the project | Description | Research interests |
| Eleanor Spaventa | research interests > EU Constitutional law; EU Fundamental Rights; Common Foreign and Security Policy; EU internal market and Union citizenship; EU Institutional law. | ||
| Supervisor | Title of the project | Description | Research interests |
| Nilanjana Dutt | LIFTEU | Lobbying in Europe | Strategy, Lobbying, Sustainability, Firm Performance, Innovation |
| Cedric Gutierrez | Entrepreneurial decision-making; Entrepreneurial finance; Incentive systems; Decision-making under uncertainty and time; Gender and organizational inequality | ||
| Dovev Lavie | AI Agent Simulation of a Prosocial Market Digital Platform | This novel project proposes a solution to economic inequality by testing a design for a new economic system. Contrary to established remedies such as regulation, legislation, and antitrust enforcement, among other policies for reforming the current economic system, the project advocates a new economic system, namely the Prosocial Market System. This system, designed as a digital platform ecosystem, can overcome some caveats of the current system which facilitates and reinforces opportunistic behavior. The project relies on research in behavioral economics that uncovers heterogeneity in individuals’ inclinations for prosociality. The theory suggests pragmatic means to instigate and reinforce prosocial behavior while driving out opportunistic behavior in economic exchange. Accordingly, the platform prioritizes societal values over profit making and utility maximization, which can help cope with economic inequality. Novel design principles include community-centered exchange and differential pricing whereby high-income consumers subsidize low-income consumers. The system also imposes limits on consumption and vendors’ profit, with excess profit redistributed to consumers. The underlying logic is that prosocial behavior pays off emotionally despite its associated economic costs. The project involves design of software algorithms that emulate the economic system, computer simulation using AI agents, and a field experiment that tests the feasibility and stability of the system. The analysis can help optimize system parameters and facilitate future implementation of the prosocial market system. The project contributes to interdisciplinary research on societal grand challenges, prosociality, and digital platforms. The MSCA position is for a young researcher in computer science or related fields, with skills in systems analysis and design, programming (Python), and AI agent simulation. The researcher will be involved in tasks such as systems analysis, hardware and communication system design, programing of administrator, vendor, and consumer modules, interface with payment solutions, testing of the software, designing and running simulations in the course of product development, coordination with outside software companies that may be involved in the development, and technical support during the field experiment. The researcher will also be involved in the literature review, analysis of findings, and writeup of academic papers. The assignments can be adjusted based on the background and skills of the candidate. |
Digital platforms, Prosocial behavior, Economic system, societal challenges, AI simulation |
| Pier Vittorio Mannucci | Creativity, Social Networks, Careers, Idea Journey, Culture | ||
| Felix Poege | From Science to Innovation | The prospective research projects cover the interactions between science and corporate innovation. Of specific interest is research into understanding the impact of corporate decisions on the trajectories of scientific research and the transition of individuals from a purely scientific orientation towards applied engineering and commercialization-oriented innovation within companies. For this purpose, a large-scale dataset covering the labor market biographies of scientists and engineers in universities and in industry has been developed. These topics are highly relevant to answer questions in strategic management, as the importance of effectively absorbing and commercializing scientific knowledge has increased with the declining contribution of the corporate sector itself to basic research. Firms’ engagement with science appears to shape their competitive advantage in strategic sectors such as biotechnology and computer science—especially within the field of artificial intelligence. The persistent weakness of European industry in successfully capitalizing on strong European research (often referred to as the European Paradox) in these areas further underscores the importance of these topics in Italy and, more broadly, across Europe. | Innovation,Science,R&D,Inventors |
| Supervisor | Title of the project | Description | Research interests |
| Kai Zhu | How AI-powered Search Shapes What We Think About Brands | This research project explores how large language models (LLMs) retrieve and cite information for brand and product queries. The study examines the frequency, quality, and reliability of sources referenced by LLM-based search engines, probing whether these automated systems favor authoritative brand content or inadvertently promote less credible, outdated, or even “hallucinated” references. By delving into the patterns of information sourcing behavior across different platforms, the research seeks to uncover potential biases in how brands are represented—shedding light on the mechanisms that shape consumer perceptions and ultimately influence brand reputation. At its core, the project poses an important question: How do AI-driven search engines affect the way consumers receive and trust brand-related information, and what are the implications for SEO and brand management strategies? Simultaneously, it addresses an AI question concerning the transparency and accountability of LLM-based systems in handling dynamic and competitive information environments. The findings promise to offer empirical insights that not only enhance our understanding of AI’s role in the modern information ecosystem but also inform strategic recommendations for marketers aiming to optimize brand visibility and control in an era where AI-generated narratives increasingly shape consumer decision-making. |
Computational Social Science, text as data, artificial intelligence |
| Supervisor | Title of the project | Description | Research interests |
| Ala Alrababah | research interests > immigration and refugees | ||
| Grace Ballor | research interests > economic history, international history, business history, European Union, European integration, global governance, global capitalism, climate change | ||
| Italo Colantone | The political sustainability of the green transition | Responding to climate change requires effective policy action. In democracies, enacting climate policies requires broad public support and chiefly electoral backing for parties and candidates proposing ambitious climate action. Understanding the politics of climate change is thus crucial to ensure successful mitigation action that is politically sustainable in the long term. My project delves into these issues. | Green Transition; Globalization; Artificial Intelligence; Political Implications of Structural Economic Changes |
| Stefania Gerevini | Art and Politics in the Medieval Mediterranean | I would be available to supervise projects invested in the nexus between arts and politics in the medieval Mediterranean, with specific focus on artistic interactions, political conflict, and public memories (C12-14); and on the modern historiographies of medieval and Byzantine art. | |
| Giovanna Invernizzi | Party Organization and Political Selection | This project investigates how party organizational structures influence the selection of political candidates, affecting both quality and representativeness in democratic systems. Using formal modeling and causal inference methods, it will examine the trade-off between traditional measures of candidate quality (education, expertise, experience) and descriptive representation. | Political Institutions, Parties, Party Organization |
| Alessia Melegaro | Modeling Behavioral Inequalities in Epidemic Dynamics | This project aims to investigate differences in epidemic-relevant behaviors—such as mask-wearing, remote work adoption, mobility reduction, contact patterns, and vaccination uptake—across socio-economic groups. Building on existing mathematical models of infectious disease spread, it seeks to integrate these behavioral differences to improve predictive accuracy and scenario analysis. Leveraging large-scale, population-representative surveys conducted in Italy, France, Germany, UK, Spain, Hungary, the project will calibrate epidemic models that explicitly account for structural inequalities. This framework will enable the quantification of how behavioral disparities shape epidemic trajectories and support the design of more targeted and equitable public health interventions. | Epidemiology, infectious diseases, global health |
| Greta Nasi | Advancing Europe's Strategic Digital Autonomy through AI | Artificial Intelligence is becoming the cornerstone of economic, geopolitical, and societal transformation. While the United States and China dominate AI innovation through scale and investment, Europe faces a crucial inflection point. This project explores how the European Union can align fragmented national initiatives into a cohesive, public-purpose-driven AI strategy. Drawing on interdisciplinary insights and policy analysis, the research will examine how to build scalable infrastructure, foster open and mission-oriented research ecosystems, and enable strategic investments across sectors such as healthcare, energy, and public services. The goal is to define actionable policy frameworks that link AI development with Europe’s values of social inclusion, democratic governance, and technological sovereignty. By investigating mechanisms for funding, interoperability, and governance, this project will deliver strategic recommendations for a coordinated European AI policy that is both purposeful and scalable. The postdoc researcher will analyze AI policy strategies across the EU, US, and China, focusing on governance, funding, and implementation. They will map EU initiatives, identify gaps, and engage stakeholders to shape a coordinated, mission-driven AI policy. The role includes producing scientific publications, policy recommendations, and supporting expert workshops across Europe. |
innovation in public services, gov tech, cybersecurity |
| Paola Profeta | Research on Gender Equality | Investigate the gender gaps in society, economy and politics. Effects of policies and firms' interventions. | Gender, Politics, Public economics |
| Tamas Vonyo | Spoils of War: The Economic Consequences of the Great War in Central Europe | Combining methods of historical economic geography and comparative business history, we exploit rich data on economic development at regional and firm level to study the impact of imperialism the war on industrialization and industrial enterprise. | Economic History, Modern European History, Economic Growth, Industrialization, Socialism |
| Supervisor | Title of the project | Description | Research interests |
| Daniel Gros | The resurgance of discriminatory trade polices | Until recently, a key pillar of the global trading system was the WTO with its most favoured nation clause. Over the last years many countries have increasingly used trade policies for geo-political aims. These policy instruments (tariffs, export bans, etc.) are by their nature discriminatory as they apply only to one trading partner. There is relatively little research on the impact of discriminatory trade policies because they require at least a three country model. This project should investigate what standard models of trade imply for the costs and benefits of discriminatory trade policies. Trump tariffs provide one example, but sanctions should also be considered. | International trade, European integration, industrial policy |
Testimonials
Andrea Morrison
GOTaM Cities - Geography Of Talents in Metropolitan Cities
"The MSC fellowship at Bocconi gave me the opportunity to deepen my research interests, expand my collaboration network and overall boost my career prospect. Bocconi proved to be the ideal place to develop all this, I got great support and felt part of a global community of excellent researcher."
Lavinia Piemontese
FIBRE - FIrm Behavior in Rough Environments
"Thanks to the Marie Skłodowska-Curie Fellowship, I had the chance to relocate to my home country and join a great research unit (CLEAN) within the vibrant community of Bocconi. Besides substantially improving my research network, this fellowship allowed me to travel and acquire many useful resources. My academic career will definitely benefit from these 24 precious months!"
Gábor Scheiring
How is Populism and Health Associated in Europe (PHASE)?
"The MSC Fellowship is about opportunities. Opportunity to expand my research, invest in training, get coaching, visit conferences, and leave an imprint. And at Bocconi, I received all the academic and administrative support I needed to realize these opportunities. These past two years have been an absolute game-changer."
Dennis Verhoeven
DIV_INV - Knowledge Diversity Building by Inventors
"The Marie Skłodowska-Curie Fellowship has allowed me to pursue a project close to my heart in the vibrant academic environment of Bocconi."