Longitudinal Dropout Prediction
[Closed]
Work description
1. Contextualisation of the education landscape in the European Union; 2. Literature review, as thorough as possible; 3. Identification of the knowledge gap that the dissertation aims to cover; 4. Collection and processing of data relevant to the problema; 5. Implementation of TabPFN and comparison with the state-of-the-art; 6. Analysis of the results; 7. Discussion of the results; 8. Write the report about the work developed.
Academic Qualifications
Mestrado em Ciência da Computação.
Minimum profile required
Bachelor Degree in Computer Science. Attendance of PhD's Degree in Data Science and Computation. Oral and written communication skills in Portuguese lanaguage.
Preference factors
Good knowledge of the English language.
Application Period
Since 05 Mar 2026 to 18 Mar 2026
[Closed]
Centre
Industrial & Systems Engineering and Management