Bocconi University | Postdoc on Personalized and Subjective approaches to Natural Language Processing

Research Project

PERSONAE will make language technology (LT) accessible and valuable to everyone. It will revolutionize research in subjective tasks in NLP such as abusive language detection and sentiment and emotion analysis by developing a new field called personal NLP, yielding new datasets, tasks, and algorithms. This new research area will explore subjective tasks from the perspective of the individual as information receiver, making users active actors in the creation of LTs instead of mere recipients. This will allow for a more tailored, effective approach to NLP model design, resulting in better models overall. Each person has their own interests and preferences based on their background and experience. These factors impact their views of what makes them happy, angry, or depressed over time. Language technologies (LTs) can consider individual preferences. However, current research presumes a static view of subjectivity: that a single ground truth underlies subjective tasks such as abusive language detection, an assumption that lacks human variability and prevents universal access to LTs. Language-based AI such as virtual assistants is widely available. But despite significant scientific advances, most LT applications are inaccessible to individuals and their public’s opinion has become increasingly negative. GPT-3’s 2020 release boosted business-oriented applications such as copywriting and chatbots, yet few that let people improve their lives—for example, by controlling what they see on social media. This gap becomes more pronounced for subjective tasks. PERSONAE will design subjective LTs that can be adapted by individuals at will over time. Based on an ambitious meta approach able to generalize from existing, disconnected work, PERSONAE will rely on fully personalizable privacy-aware algorithms that can be used by anyone. It will reveal benefits of LT far beyond those of existing systems, paving the way for future applications.

Responsibilities in the Project

Successful candidates will actively collaborate with the research team to develop and implement new algorithms and methodologies in the field of Natural Language Processing (NLP). Primary responsibilities include participating in the design and execution of experiments to evaluate the effectiveness of personalized NLP models, exploring and analyzing data, collaborating on the creation and curation of annotated datasets, and writing scientific papers.

Successful candidates will need to demonstrate:

• proven experience in Natural Language Processing (NLP), with a focus on subjective tasks and model personalization.
• programming skills in languages such as Python and expertise in the use of NLP frameworks such as PyTorch.
• experience in publishing papers in leading conferences in the field of computational linguistics.

Applicants should attach to their application a list of publications and a motivation letter.

Elegibility

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.

Applicants should apply by submitting the complete package via our on-line application system, which can be found at https://jobmarket.unibocconi.eu/?id=1004 by 23:59 of 13th November 2026 (Italian time).

Each candidate’s application must clearly indicate:

• surname and name
• date and place of birth
• citizenship
• residence
• contact address

The application must include the following documents, which must be attached to the application:

• professional C.V., including a list of any titles/qualifications and publications, in pdf format;
• any publication, or document that the candidate intends to submit for evaluation, in pdf format, up to a maximum of 10 scientific publications;
• a motivation letter

For any problem related to uploading files, the candidate can contact faculty@unibocconi.it

Application and more details: https://jobmarket.unibocconi.eu/?id=1004