Positions: 6

Research Grant (BI)

  • Project PT Smart Retail–RefªC6632206063-00466847-BI|2024/529

    Type of position: Research Grant (BI)
    Duration: 6 months
    Deadline to apply: 2024-05-09
    Description

    The goal of this project is to contribute to the development of advanced security and privacy-preserving technologies for smart-retail stores. Specifically, this project aims to study an emerging class of vulnerabilities named Denial of Wallet (DoW) attacks. In this type of attack, attackers can exploit vulnerabilities in cloud-hosted services that can trigger excessive resource usage, such as external APIs or public storage, resulting in financial damage to smart retail actors that rely on the cloud for hosting their web applications. Considering these attacks, this project has the following main goals: (1) Design and implement DoWGuard, a novel detection tool for DoW vulnerabilities in cloud applications; (2) Extend the existing static analysis techniques to include the ability to reason about economic sinks and interactions with cloud APIs. (3) Define and specify queries within DoWGuard to accurately identify DoW vulnerability patterns. (4) Integrate DoWGuard into the CI/CD toolchain, providing developers with immediate feedback on potential DoW vulnerabilities during the development lifecycle. (5) Evaluate DoWGuard's effectiveness by applying it to real-world cloud applications. The expected outcome of this project includes both a report of the analyzed solutions and a software prototype of the implemented solution.


    Contact email: rh@inesc-id.pt

  • Project ACCELERAT.AI – refªC644865762-00000008-BI|2024/527

    Type of position: Research Grant (BI)
    Duration: 4 months
    Deadline to apply: 2024-05-06
    Description

    A significant number of transformer-based language models specifically tailored for European Portuguese have been recently proposed, such as Albertina, Gervásio or Glória, among others.  These type of models have shown exceptional modelling capabilities of language (understanding and generation) and remarkable performance on a wide range of natural language processing tasks. Concurrently, a similar effort by the research community has resulted in the proposal of several foundation models for speech and audio. These models are trained on extensive amounts of multilingual data to acquire robust representations that capture the intrinsic structure and relationships within speech and audio signals.

    The goal of this project is to delve into the existing Portuguese language model landscape, conducting comparative analyses and assessing their potential utility. The final aim is to integrate these models into an automatic speech recognition system. This system will employ a pre-trained speech encoder, one of the studied pre-trained large language models (utilizing either encoder-decoder or decoder-only configurations), and a neural adaptor module.  

    The work plan includes the following steps:

    1. Research existing foundation models for European Portuguese, both text and speech/audio.

    2. Analyse and compare them in common benchmarks.

    3. Assess their potential utility as a part of an ASR pipeline that integrates both pre-trained speech encoders and LLMs.


    Contact email: rh@inesc-id.pt

  • Project ATE – refª C644914747-0000023-BI|2024/526

    Type of position: Research Grant (BI)
    Duration: 6 months
    Deadline to apply: 2024-04-26
    Description

    This work is focused on the Ethernet synchronization protocol named PTP (Precision Time Protocol - IEEE 1588:2019). To be used in an Ethernet switch under development, the main feature to be implemented is the "Transparent Clock" mode, supporting the following modes: peer-to-peer, end-to-end, one-step and two-step corrections modes. The functionality must be described in Verilog, targeting an implementation using FPGAs from Intel/Altera. The implementation shall be validated by logic simulation. The validation in a real environment will depend on the availability of an Ethernet network with support for PTP.


    Contact email: rh@inesc-id.pt

  • GAIPS - BI|2024/525 - UIDB/50021/2020 (DOI:10.54499/UIDB/50021/2020)

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2024-04-24
    Description

    1) Provide system maintenance and manage the group’s technical assets. This includes: the overall management of the group server, associated repositories and related web services; the overall management, inventory and maintenance supervision of the group’s assets, and; periodically performing backups and security updates.

    2) Deploy and manage a set of collaboration-based knowledge-sharing and development tools and services for the group projects. These tools will aim at improving existing collaboration protocols both within and between project in terms of knowledge sharing as well as code reuse.

    3) Develop an application supporting the management of teams during task execution based on individual interaction preferences. This application is aimed at being reusable in different contexts by the group.


    Contact email: rh@inesc-id.pt

  • Proj. CRAI – Refª C628696807-00454142-BI|2024/524

    Type of position: Research Grant (BI)
    Duration: 6 months
    Deadline to apply: 2024-04-24
    Description

    The successful applicant will participate in the research and development activities of the REST-FL project (Research on Key Technologies for Epidemic Spatio-Temporal Modeling using Cross-Country Federated Learning), with an emphasis on the development and deployment of geostatistical models for pandemic modeling. This work will be integrated in a team of 6-8 people, who will create and deploy models for the prediction of epidemic diseases in Portugal, Macau and mainland China.


    Contact email: rh@inesc-id.pt

Contract