Positions: 11

Research Grant (BII)

  • Refª BII|2025/675 - Project InfraGov - Refª 2024.07411.IACDC

    Type of position: Research Grant (BII)
    Duration: 6 months
    Deadline to apply: 2025-03-10
    Description

    ONE (1) research grant for students enrolled in a BSc programme with reference number BII|2025/675 under the scope of the Project InfraGov: A Public Framework for Reliable and Secure IT Infrastructure – Refª 2024.07411.IACDC funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    The selected candidate will be a member of the research project InfraGov, which aims to develop the first language-agnostic solution for reliable analysis and automated repair for Infrastructure as Code that also uses recent developments in generative AI for reducing the time from vulnerability disclosure to mitigation.

     

    The selected candidate will:

    1) Contribute to the software implementation of the InfraGov toolchain

    2) Produce a technical report documenting all the tasks performed


    Contact email: bolsas@inesc-id.pt

  • Refª BII|2025/674 - Project InfraGov - Refª 2024.07411.IACDC

    Type of position: Research Grant (BII)
    Duration: 6 months
    Deadline to apply: 2025-03-10
    Description

    ONE (1) research grant for students enrolled in a BSc programme with reference number BII|2025/674 under the scope of the Project InfraGov: A Public Framework for Reliable and Secure IT Infrastructure – Refª 2024.07411.IACDC funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    The selected candidate will be a member of the research project InfraGov, which aims to develop the first language-agnostic solution for reliable analysis and automated repair for Infrastructure as Code that also uses recent developments in generative AI for reducing the time from vulnerability disclosure to mitigation.

    The selected candidate will:1) Contribute to the software implementation of the InfraGov toolchain2) Produce a technical report documenting all the tasks performed


    Contact email: bolsas@inesc-id.pt

Research Grant (BI)

  • BI|2025/676 - Project EquiVet.AI - Refª 2024.07265.IACDC/2024

    Type of position: Research Grant (BI)
    Duration: 4 months
    Deadline to apply: 2025-03-11
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/676 under the scope of the Project EquiVet.AI with the refª 2024.07265.IACDC/2024 funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    The candidate will be working in Task 5:  The Prototype

    This task encompasses the comprehensive engineering and iterative development required to assemble the components of our AI-based diagnostic and report-writing system developed in the previous tasks. After each component has been developed and tested individually, task 5 will allow their integration into a cohesive prototype. The prototype will incorporate our trained models for analyzing videos and images of horses, as well as models for generating veterinary reports from audio or text inputs. Veterinarians will interact with the AI models through an intuitive user interface. This interface will allow users to upload videos, images, and text, receive model predictions, and provide feedback. The interface will display potential diagnoses and generate reports for validation by veterinarians. Feedback can be provided by approving or correcting predictions and offering additional insights, which will be used to refine the models. The prototype will feature a user-friendly interface designed for ease of use by veterinarians. The design will focus on clarity and accessibility, ensuring that veterinarians can quickly and easily interact with the system. User experience testing will be conducted to gather feedback on the interface design and make necessary adjustments. The final step involves integrating all the components into a cohesive system. This includes linking the ASR, video and image analysis, data processing, and user interface modules.


    Contact email: bolsas@inesc-id.pt

  • Refª BI|2025/677 - Project EquiVet.AI - 2024.07265.IACDC/2024

    Type of position: Research Grant (BI)
    Duration: 4 months
    Deadline to apply: 2025-03-11
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2025/677 under the scope of the Project EquiVet.AI with the 2024.07265.IACDC/2024, funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    The candidate will participate in the tasks of: a) Gathering and Annotating Information Sources; b) Developing the Prototype.

    However, the main focus will be in the project Task 4: Writing the Medical Reports.

    The ultimate goal of Task 4 is to create a system that can generate high-quality veterinary reports with minimal human intervention, freeing up valuable time for veterinarians to focus more on patient care rather than administrative tasks.

    We aim to enhance veterinary report writing by leveraging Large Language Models (LLMs). We will use initial medical notes (audio or text) and forms and we intend to test different prompt strategies, but also to fine-tune state-of-the-art LLMs veterinary texts to capture idiosyncrasies and the style typical in veterinary documentation

    A critical aspect of this task is the continuous improvement of the LLMs through implicit and explicit human feedback. Implicit feedback will be gathered from the usage patterns and corrections made by veterinarians as they interact with the generated reports, while explicit feedback will be collected through structured surveys and direct input from users. This feedback loop will be instrumental in refining the models.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/678 - Project EquiVet.AI - 2024.07265.IACDC/2024

    Type of position: Research Grant (BI)
    Duration: 4 months
    Deadline to apply: 2025-03-11
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/678 under the scope of the Project EquiVet.AI with the 2024.07265.IACDC/2024 funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    The candidate will participate in the tasks of: a) Gathering and Annotating Information Sources; b) Developing the  Prototype.

    However, the main focus will be in the project Task 3: Diagnostic Support. Our initial focus on diagnosing asthma in horses will be expanded to encompass other respiratory conditions, including pneumonia and pleurisy. By refining our video-based approach, we aim to detect signs of equine pneumonia and pleurisy by identifying specific breat patterns and abdominal movements. We will enhance our asthma detection model to distinguish it from pneumonia and pleurisy, addressing the challenge of differentiating between these conditions. Accurate differentiation will help reduce the misuse of antibiotics, as improper treatment often results from misdiagnosis. Additionally, we aim to identify various types of skin reactions, from mild irritations to severe allergic responses, aiding veterinarians in differentiating between causes such as IBH, atopic dermatitis, food-induced dermatitis, mycosis and parasitic infections. To achieve these goals, our diagnostic models will be trained on comprehensive datasets encompassing a wide range of respiratory symptoms and skin conditions. These datasets will include high-resolution videos of horses exhibiting different stages of asthma, pneumonia and pleurisy, as well as images of various skin conditions. 

    We will also implement Active Learning strategies to enhance the model's training process. Active Learning will enable the model to identify and query the most uncertain predictions for human labeling. By focusing on these challenging cases, we can efficiently improve the model's performance with minimal additional data. This approach ensures that the model learns from the more informative examples, enhancing its diagnostic capabilities. While pre-trained models will be included, we will continue to explore feature-based methods. Feature-based methods offer a level of explainability necessary for end-users, as veterinarians require transparent and understandable diagnostic processes. These methods allow us to incorporate veterinarians' insights more easily, as specific features a patterns identified by the models can be directly linked to clinical knowledge and observations. The diagnostic support system will provide continuous monitoring of affected areas, allowing for real-time assessment and follow-up. This feature is particularly valuable for chronic conditions like asthma and IBH, where ongoing monitoring can inform treatment adjustments and track disease progression. By integrating continuous monitoring capabilities, we aim to offer a comprehensive diagnostic tool that supports both initial diagnosis and long-term management of these respiratory and skin conditions in horses.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/672 - Project InfraGov – Refª 2024.07411.IACDC

    Type of position: Research Grant (BI)
    Duration: 6 months
    Deadline to apply: 2025-03-10
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/672 under the scope of the Project InfraGov: A Public Framework for Reliable and Secure IT Infrastructure  – Refª 2024.07411.IACDC  funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    The selected candidate will be a member of the research project InfraGov, which aims to develop the first language-agnostic solution for reliable analysis and automated repair for Infrastructure as Code that also uses recent developments in generative AI for reducing the time from vulnerability disclosure to mitigation.

    The selected candidate will:1) Investigate learning-based techniques for the detection and repair of code smells and bugs in Infrastructure as Code scripts2) Contribute to the integration of techniques developed in 1) into the InfraGov toolchain3) Produce a technical report documenting all the tasks performed


    Contact email: bolsas@inesc-id.pt

  • Refª BI|2025/673- Projecto InfraGov - Refª 2024.07411.IACDC

    Type of position: Research Grant (BI)
    Duration: 6 months
    Deadline to apply: 2025-03-10
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/673 under the scope of the Project InfraGov: A Public Framework for Reliable and Secure IT Infrastructure  – Refª 2024.07411.IACDC  funded by Fundação para a Ciência e a Tecnologia, is available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    The selected candidate will be a member of the research project InfraGov, which aims to develop the first language-agnostic solution for reliable analysis and automated repair for Infrastructure as Code that also uses recent developments in generative AI for reducing the time from vulnerability disclosure to mitigation.

     

    The selected candidate will:

    1) Investigate learning-based techniques for automatically inferring Infrastructure as Code scripts from the source code of applications

    2) Contribute to the integration of techniques developed in 1) into the InfraGov toolchain

    3) Produce a technical report documenting all the tasks performed


    Contact email: bolsas@inesc-id.pt

  • BI|2025/671 - Proj CRAI - Refª C628696807-00454142

    Type of position: Research Grant (BI)
    Duration: 4 months
    Deadline to apply: 2025-03-10
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2025/671 under the scope of the Project Center for Responsible AI – Refª C628696807-00454142 funded by by Recovery and Resilience Plan (RRP) https://recuperarportugal.gov.pt/ and Next Generation EU European Funds, is available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    The grantee will work on the development of a scale to measure the human perception of an AI agent in the continuum of a full team member or just a tool. The grantee will also collaborate in the definition, execution and analysis of user studies in the topic of human-AI collaboration..


    Contact email: bolsas@inesc-id.pt

Contract