Research Fellowship in AI and Data Science for Cybercrime Prevention
Join the Tools4LEAs-v3 project at ISEL to develop AI-driven technological solutions for law enforcement against cybercrime.
Best for:Best for recent computer science graduates with strong Python and machine learning skills looking to apply AI to cybercrime prevention.
Overview
The Instituto Superior de Engenharia de Lisboa (ISEL) is offering a 14-month research fellowship within the Tools4LEAs-v3 project. The successful candidate will join a research team dedicated to developing advanced technological tools that assist law enforcement authorities in combating cybercrime. The work involves core phases of fundamental research, system architecture design, technical execution, and experimental validation using artificial intelligence and machine learning models. Applicants are expected to work on-site at ISEL in a controlled environment, maintain strict confidentiality, and align their research work with a master's thesis or final project.
What you'll do
- Conduct fundamental research, define problem statements, and analyze state-of-the-art technologies for cybercrime prevention.
- Design system architecture, define software components and interfaces, and formulate detailed implementation plans.
- Develop algorithms, machine learning models, and proof-of-concept software prototypes in a controlled environment.
- Execute experimental validations, evaluate system performance, and ensure compliance with GDPR and FAIR data principles.
- Prepare final reports, technical documentation, and future research recommendations, coordinating tasks with a master's dissertation.
Requirements
Degree required: BSc in Informatics and Multimedia Engineering, Informatics and Computer Engineering, Computer Science, Data Science, or a related field
Language: Portuguese and English; fluency required in both
Instruction: Portuguese and English
- Demonstrated programming proficiency in Python
- Experience in developing machine learning and deep learning models
- Prior creation of a software application or system integrating AI models, demonstrated via coursework, code repositories, or publications
- Availability to work on-site at ISEL facilities in Lisbon
- Willingness to sign a data and results confidentiality agreement
- Must hold a bachelor's degree in a relevant field
- Must be enrolled in a master's degree program, PhD program, or a non-degree educational course at a higher education institution for the 2026/2027 academic year
- Must adhere to the exclusive dedication regime required by the fellowship regulations
Funding & terms
How to apply
Candidates must submit their applications including all required proof of academic enrollment, CV, and supporting evidence of software development and AI integration work through the designated institutional process.
- CV
- Proof of academic enrollment
- Degree certificates
- Curricular unit report or code repository demonstrating AI software development
- Honor declaration of eligibility
Contact
Pedro Mendes Jorge· Jury President
Create a free profile to unlock your personal match score, the full requirements, funding details and how to apply — in English or Persian.