Positions: 9

Research Grant (BI)

  • BI|2026/866 - Projet CCLoud

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2026-03-17
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2026/866 under the scope of the Project CCLoud with the refª 2023.16986.ICDT, funded by Fundação para a Ciência e a Tecnologia I.P., is now available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    To conduct an in-depth study of interplay between carbon efficiency and performance in serverless Function as a Service (FaaS) platforms.

    Investigate how low-latency and high-throughput function designs affect total carbon footprint. Assess how incremental performance improvements impact the energy spent per invocation and total system power, and the embedded carbon intensity associated with the hardware utilized will be factored in to determine both energy and carbon-efficiency. Determine efficiency curves and identify thresholds beyond which performance tuning yields diminishing returns relative to carbon cost. Integrate work outcomes in an understandable model that users (FaaS developers) and providers can employ to balance latency and carbon footprint.


    Contact email: bolsas@inesc-id.pt

  • BI|2026/868 - Projet CCLoud – refª 2023.16986.ICDT

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2026-03-17
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2026/868 under the scope of the Project CCLoud with the refª 2023.16986.ICDT, funded by Fundação para a Ciência e a Tecnologia I.P., is now available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    To conduct an in-depth study of graph processing considering energy efficient and carbon intensity in edge-cloud and cloud-continuum scenarios.

    Investigate the implications of current movements to push the cloud towards the edges of the networks, where big, remote, energy-hungry datacenters are combined with more widespread edge infrastructures where data can be processed with reduced latency and increased privacy.

    Assess how a decentralized graph storage and processing system can be made aware of computational limitations. Combine the graph processing engine with peer-to-peer storage for decentralization. Evaluate the implications in latency and throughput when processing is performed at the same location as the data, when possible, and how this can contribute to increased energy efficiency and reduced carbon intensity.     


    Contact email: bolsas@inesc-id.pt

  • BI|2026/867-Projet CCLoud – refª 2023.16986.ICDT

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2026-03-17
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2026/867 under the scope of the Project CCLoud with the refª 2023.16986.ICDT, funded by Fundação para a Ciência e a Tecnologia I.P., is now available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    To conduct an in-depth study of interplay between carbon efficiency and performance in workflow/dataflow execution in cloud platforms.

    Investigate how workflow-based applications are widely used in cloud and cluster environments to coordinate complex computations, including AI workloads, with increasing energy and carbon footprints. Assess how carbon-aware scheduling techniques such as shifting workloads in time, across space, migrating them across regions, or adjusting allocated resources can significantly reduce emissions. Combine the application of such techniques, often employed only isolated. Develop a carbon-aware workflow execution framework capable of integrating real-time carbon intensity information into workflow scheduling decisions.


    Contact email: bolsas@inesc-id.pt

  • BI|2026/861 - Project GLOG

    Type of position: Research Grant (BI)
    Duration: 12 months
    Deadline to apply: 2026-03-09
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2026/861 under the scope of the Project GLOG – Refª 2023.18452.ICDT/ LISBOA2030-FEDER-00771200, funded by FEDER, operation nº 16539 - MPr-2023-12, Balcão dos Fundos and FCT, is now available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    The goal of this work is to develop a geo-distributed transactional storage based on shared logs design. 

    The student must design, prototype, and evaluate a geo-distributed storage system and write its findings in a scientific paper to be submitted at a conference.

    As such, the work is divided into 4 key steps:

        1. State-of-the-art Revision and design proposal. 2 Months

        2. Development of the prototype. 6 months

        3. Deployment and Evaluation of developed prototype. 2 months

        4. Writing and submission of scientific paper. 2 months


    Contact email: bolsas@inesc-id.pt

  • BI|2026/859 - Project IWGDM/CoUDLabs

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2026-03-06
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2026/859 under the scope of the Project IWGDM/CoUDLabs - funded by INESC ID, is now available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    1. Data harmonisation framework: design and prototype a pipeline to map multi-source water utility data into a consistent, documented target model (schemas +semantics).

    2. KAG-based assistance: develop KAG components that support (semi-)automatic harmonisation tasks such as field mapping, entity resolution, unit/format normalisation, and metadata enrichment.

    3. Quality and traceability: implement mechanisms for provenance, confidence scoring, and human-in-the-loop review.

    4. Validation on real data: evaluate on representative datasets and realistic harmonisation scenarios with measurable quality and efficiency gains.

    5. Deliverables for reuse: produce code, documentation, and reproducible experiments suitable for internal adoption and MSc thesis work. 


    Contact email: bolsas@inesc-id.pt

  • BI|2026/862 - ATE

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2026-03-06
    Description

    ONE (1) research grant for students with Master degree with reference number BI|2026/862 under the scope of the Project ATE – Refª C644914747-0000023 funded by funded 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 objective of this grant position is to support the research team of ATE-PRR in activities related to the development of the final NILM solution integration, including the following tasks: 

     

    Task 1: Finish the development of a printed 3D plastic enclosure to hold the NILM module (2 weeks)

    a)  Iterate the design following previously performed tests.

    b)  Implement and test the new design of the enclosure.

     

    Task 2: Plan the required steps leading to deployment and testing of NILM hardware and software (4 weeks)

     

    a)  Propose a test setup for the NILM module using high-power signals, including equipment list and required instrument software.

    b)  Develop the required test scripts in Python/Matlab.

    c)   Propose a test plan and a test setup using semi-automated test procedures.

     

    Task 3: Test procedure validation (6 weeks) 

     

    a)  Conduct the proposed test plan on representative use cases.

    b)  Adjust the test plan for final deployment.


    Contact email: bolsas@inesc-id.pt

  • BI|2026/860 - Project LeaF – Refª 2024.14611.CMU

    Type of position: Research Grant (BI)
    Duration: 6 months
    Deadline to apply: 2026-03-05
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2026/860 under the scope of the Project Machine Unlearning in Speech Foundation Models: Learning to Forget (LeaF), Refª 2024.14611.CMU , funded Fundação para a Ciência e a Tecnologia, I.P., is now available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    Development and evaluation of machine unlearning algorithms for speech foundation models against jailbreak attacks, including:

    - Selection and preparation of models and datasets to be used in the project's experiments.

    - Benchmarking jailbreak attack success against speech foundation models.

    - Development of gradient-based approximate machine unlearning approaches.

    - Evaluation of the developed machine unlearning approaches with regard to the mitigation of jailbreak attacks.


    Contact email: bolsas@inesc-id.pt

Contract