巴西坎皮纳斯大学招聘博士后—计算机科学（教学技术+人工智能）

Post Doctoral Position in Computer Science (Technology for Teaching + AI)

University of Campinas - UNICAMP

Date Posted: Posted on 26 May 2026

Location: Brazil

Salary: $2,500 - $2,500

Job Tags:

artificial intelligence, computer science, Higher Education

Postdoctoral Fellowship Opportunity in Computer Science at UNICAMP

The Institute of Computing at the University of Campinas (UNICAMP) is seeking a highly motivated Postdoctoral Fellow to join our research team. This position focuses on the project “Techniques for Extracting Concept Inventories from Semi-Open Questions,” funded by FAPESP (São Paulo Research Foundation) under grant number 2025/19399-8.

Fellowship Details:

– Duration: 36 months

– Monthly Stipend: R$ 12.570,00 (Brazilian Reais)

– Start Date: As soon as possible, with a preference for candidates available to start by June/2026.

– Eligibility: Candidates must have a Ph.D. in Computer Science or a closely related field, with a strong background in educational data analysis, machine learning, and natural language processing.

About the Project

One of the core challenges in developing concept inventories is converting a dataset of student responses from semi-open questions into actionable misconceptions. This project aims to document these specific lines of student thinking and use them to generate robust multiple-choice questions. These newly generated questions will then be validated and analyzed collectively as a comprehensive concept inventory.

Given the complexity of generating these hypotheses and the ultimate goal of generalizing these tools across multiple distinct fields (at least two different areas), this role requires the advanced expertise of a postdoctoral researcher.

Key Objectives and Responsibilities

The selected candidate will work on tasks aligned with the main project schedule, with a focus on:

1. Data Collection: Gathering and organizing data from the administration of semi-open questions.

2. Methodology Development: Creating framework methodologies to generate hypotheses based on incorrect student answers.

3. Cataloging and Clustering: Grouping and cataloging incorrect responses across multiple questions based on similar lines of thought.

4. Distractor Generation: Designing multiple-choice question distractors (wrong answer choices) derived from the identified misconceptions.

5. Evaluation: Assessing and validating the final Concept Inventory.

Supervisor and Institution

Supervisor: Prof. Rodolfo Azevedo

Institution: Institute of Computing (IC), UNICAMP, Brazil

How to Apply

Interested candidates should send their application by email, including:

– Curricular Summary (https://fapesp.br/6351/instructions-for-the-elaboration-of-a-curricular-summary)

– Application Letter

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