Bocconi University 
Milano, Italy Project Description
Milano, 23/09/2026 prot. n. 226112 CALL FOR APPLICATIONS FOR THE AWARD OF 1 POST-DOC RESEARCHER FIXED-TERM EMPLOYEE CONTRACT, PURSUANT TO ART. 22, PARAGRAPH 3 OF LAW N.240/2010 AMENDED BY LAW N. 79 OF 29TH JUNE 2022, FOR THE SCIENTIFIC DISCIPLINARY GROUP 09/IINF-05 INFORMATION PROCESSING SYSTEMS, AT THE DEPARTMENT OF COMPUTING SCIENCES OF UNIVERSITA’ COMMERCIALE “LUIGI BOCCONI” OF MILAN. Article 1 Call for Competition To promote the education and improvement of junior scholars, Università Commerciale “Luigi Bocconi” of Milan, announces a competition by exams and academic titles for the award, by means of an appropriate contract, pursuant to art. 22 of Law 240/2010, amended by Law n. 79 of 29th June 2022, and using the relative University Regulations emanated with the Rectoral Decree n° 106 of 21th December 2022, of 1 Post-doc Researcher Position with the following characteristics: Duration: 24 months (renewable for an additional 2 years) Possible starting date: 1st January 2027 At the Department of Computing Sciences of Bocconi University Scientific Disciplinary Group: 09/IINF-05 INFORMATION PROCESSING SYSTEMS Scientific Disciplinary Sector: IINF-05/A Information Processing Systems Project: “E4RL: Egocentric 4D Representations for Robot Learning” Financed by: Tech Europe Foundation (TEF) Professor of reference: prof. Chiara Plizzari Research Project Today, robots are usually trained either in manually designed simulations or through expensive robotcollected experience. Human videos offer a powerful alternative. They are easy to collect, widely available, and show people performing many everyday skills that we would like robots to learn. However, videos are not directly useful for robot learning. A video is only a sequence of 2D images. It shows what happened, but it does not explicitly tell the robot how the person interacted with the physical environment: where relevant objects and scene elements are in 3D, how they move, how they are used, or which of them matter for completing a task. E4RL will address this gap by converting first-person videos into egocentric 4D representations for robot learning. Here, “first-person/egocentric” means that the video is recorded from the point of view of a person performing the task, for example using a wearable camera. “4D” means that the system builds a 3D representation of the physical scene and tracks how it changes over time. In other words, E4RL will turn videos of human activity into dynamic 3D descriptions of the physical world that robots can use for learning. Specifically, E4RL will recover three complementary elements from first-person video: (i) the scene structure, (ii) the objects involved in the activity, and (iii) the pose and motion of the person. The goal is to recover not only what is present, but where scene elements and objects are, how they move, how they are used, and how
they contribute to the task. These representations will be simple, interpretable, and efficient. By capturing the scene, the objects, and the human motion, they will provide robots with a structured description of how tasks are performed in the physical world. The final stage of the project will utilize those scene-object-human representations as training data for robotics policies and finally deploy the learned policies on a physical humanoid robot using only its on-board sensing and computation. This is an exciting opportunity to work at the frontier of egocentric video understanding, 3D scene representation, 4D scene understanding, and physical robot learning. The project will also benefit from the expertise of Prof. Francis Engelmann (Università della Svizzera italiana, link to bio: on compact 3D scene and object representations, and of Prof. Antonio Loquercio (University of Pennsylvania, link to bio: on robot policy learning and humanoid deployment. Responsibilities in the Project: The postdoctoral researcher will develop, implement, and evaluate new methods across the full E4RL pipeline. This includes designing and running empirical experiments, as well as defining research objectives and evaluation metrics. On the technical side, the researcher will implement and evaluate methods for recovering compact 3D scene and object representations from first-person videos, develop tracking approaches that maintain object identity and pose over time, integrate human body motion estimation into a unified scene–object–human representation, and use the resulting 4D descriptions to generate training signals for humanoid robot policies. Towards the final part of the project, the researcher will also contribute to the evaluation of learned policies both in simulation and on a physical humanoid robot. The researcher will lead quantitative and qualitative analyses, and contribute to publications at leading computer vision and robotics venues (such as CVPR, ECCV, ICCV, and IROS/ICRA). At an organizational level, the researcher will work closely with the PI, interact with PhD students in the group on related research questions, and contribute to the scientific exchanges with the external collaborators. The researcher will also contribute to the co-supervision of junior researchers.
Article 2 Admission requirements In order to participate in the competition, Candidates for the position as Post-Doc Researcher must be scholars with a PhD or equivalent qualification, obtained in Italy or abroad, or in the process of completing their PhD within six months from the date of publication of this call, with the exclusion of Professors and researchers who already hold a position with tenure, even if they have ceased service. The following are not eligible to participate in the selection procedures: permanent staff employed by universities, public research centers and institutions whose scientific specialization diploma has been recognized as equivalent to the title of research doctor pursuant to Article 74, fourth paragraph, of the Presidential Decree of 11th July 1980, no. 382; those who have benefited from contracts pursuant to Article 24 of Law 240 of 2010; those who have a degree of kinship or affinity, up to the fourth degree, with a Professor affiliated with the Department that proposed the activation of the contract, with the Rector or the Managing Director.
These statutory pre-requisites must be in place at the deadline for the presentation of applications determined by the present announcement. Applicants will obtain a conditional acceptance. At any time, the administration can arrange, with reason, exclusion from the selection procedure due to the lack of necessary pre-requisites.
Article 3 Applications Applicants should apply by submitting the complete package via our on-line application system, which can be found at jobmarket.unibocconi.eu by 23:59 of 23rd November 2026 (Italian time). Each candidate’s application must clearly indicate: • • • • • •
surname and name date and place of birth citizenship residence contact address PhD degree or expected completion date
- The application must include the following documents, which must be attached to the application:
- professional C.V., in pdf format, including a list of any titles/qualifications and publications; or — if no
- publications are available — a link to the PhD thesis;
- any publication, or document that the candidate intends to submit for evaluation, in pdf format, up to a
- maximum of 10 scientific publications;
- any patents and/or Proofs of Concept (POCs);
- a motivation letter;
- a research statement
- a list of high-profile academic referees, up to a maximum of three, to whom letters of recommendation may
- be requested.
- For any problem related to uploading files, the candidate can contact faculty@unibocconi.it.
Article 4 Evaluation Committee The Evaluation Committee for this competition, appointed by the Rector in agreement with the Dean of the Faculty and upon proposal of the Director of the relevant unit, is composed of three members, including the Principal Investigator of the Research Project, the Director of the Department or their delegate, and a faculty member/research researcher. At least one member of the Evaluation Committee must belong to the same Scientific Disciplinary Group announced in the call or to a related disciplinary group.
This is an excerpt; the full call is in the official documents below.
Call details
- Institution: Bocconi University
- Discipline sector: IINF-05/A
- Call type: Post-doc Researchers
- Call code: ID 984
- Applications open: 23-09-2026
- Application deadline: 23-11-2026
