Positions: 11

Research Grant (BII)

  • BII|2025/815-Proj. SmartRetail– refª C6632206063-00466847

    Type of position: Research Grant (BII)
    Duration: 5 months
    Deadline to apply: 2025-12-16
    Description

    ONE (1) research grant for students that are enrolled in a BSc program with reference number BII|2025/815 under the scope of the project Cen SmartRetail– refª  C6632206063-00466847,  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 goal of this project is to assess the privacy, data protection, and regulatory compliance challenges associated with smart-retail infrastructures that rely on heterogeneous hardware components. These environments inherently process personal data, device identifiers, behavioral patterns, and network metadata, which are subject to strict legal and ethical requirements under the General Data Protection Regulation (GDPR). Ensuring their correct handling is fundamental for the secure, lawful, and trustworthy operation of smart-retail stores. Considering these challenges, this project has the following main goals: 

    (1) Characterize all data flows within the smart-retail infrastructure. This includes mapping how data moves through the system – how it is captured, transmitted, processed, logged, and stored across devices. Particular attention will be given to identifying lawful bases for processing, retention needs, and potential GDPR-sensitive components.

    (2) Analyze privacy risks and evaluate compliance gaps - by studying the susceptibility of the current hardware ecosystem to GDPR violations, including risks arising from excessive data collection, insecure storage, lack of minimization, long-term retention, or insufficient access control. The analysis will incorporate principles of privacy-by-design and examine whether a Data Protection Impact Assessment (DPIA) is required.

    (3) Propose a set of data protection recommendations tailored to the smart-retail environment. These may include anonymization or pseudonymization strategies, improvements to retention policies, clearer access control mechanisms, or documentation needed for regulatory compliance and internal governance.


    Contact email: bolsas@inesc-id.pt

Research Grant (BI)

  • BI|2025/819-Project FLORA - ref. 2023.14280.PEX

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2025-12-26
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2025/819 under the scope of the Project FLORA with the ref. 2023.14280.PEX, funded by Fundação para a Ciência e a Tecnologia I.P., is now available under the following conditions:

     

    OBJECTIVES | FUNCTIONS 

    In many optimization problems, it is common to have several objective functions. However, defining an ordering of preference among these objectives might not be straightforward. In these contexts, a multi-objective optimization formulation arises with multiple Pareto-optimal solutions.

    The goal of this work is to develop new algorithms and tools to find a subset of optimal solutions that are representatives of a much larger set of Pareto-optimal solutions. To find these representatives, well-known quality indicators such as IGD+ and epsilon-indicator will be used to drive the search. 


    Contact email: bolsas@inesc-id.pt

  • BI|2025/817 / BI|2025/818-Project ATE

    Type of position: Research Grant (BI)
    Duration: 5 months
    Deadline to apply: 2025-12-22
    Description

    TWO (2) research grants for students with BSc degree with reference number BI|2025/817 - BI|2025/818 under the scope of the Project ATE – Refª C644914747-0000023 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 

    Develop tools to be used in Energy Dream Lab Support in the implementation and Setup of the Lab Support the execution of tests and simulations required in the different project Collaborate in the development of deliverables Support in the development of Scientific papers


    Contact email: bolsas@inesc-id.pt

  • BI|2025/816-Project SYNTHESIS-LISBOA2030-FEDER-00868200

    Type of position: Research Grant (BI)
    Duration: 3 months
    Deadline to apply: 2025-12-18
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2025/816 under the scope of the Project SYNTHESIS - Mosaic integration and synthetic generation of multi-omic data for the discovery of precision cancer medicines – refª LISBOA2030-FEDER-00868200, funded by operation nº 15030, Balcão dos Fundos, FEDER (Fundo Europeu de Desenvolvimento Regional) and FCT (Fundação para a Ciência e Tecnologia), is now available under the following conditions:

    OBJECTIVES | FUNCTIONS 

    This position focuses on developing generative deep learning models to integrate large-scale proteomics datasets and perform missing-value imputation. Responsibilities include designing bioinformatics pipelines for dataset processing and integration; developing generative deep learning models (including adversarial networks) and classical machine-learning methods; and building robust validation workflows across multiple independent datasets, including testing transfer-learning approaches.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/812-Proj. SmartRetail– refª C6632206063-00466847

    Type of position: Research Grant (BI)
    Duration: 5 months
    Deadline to apply: 2025-12-16
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/812 under the scope of the Project SmartRetail– refª C6632206063-00466847, 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 goal of this project is to contribute to the development of secure and privacy-preserving authentication mechanisms for smart retail environments. Modern smart retail platforms rely on cloud-hosted services and applications (mobile apps, web portals, in-store kiosks, operator tablets) that authenticate customers and staff through distributed identity frameworks compatible with OpenID/OAuth.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/803-Project ATE – Refª C644914747-0000023

    Type of position: Research Grant (BI)
    Duration: 5 months
    Deadline to apply: 2025-12-16
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/803 under the scope of the Project ATE – Refª C644914747-0000023 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 

    Support for new users of the OPAL-RT system for real-time simulation of power systems. Simulation in OPAL-RT of the functionalities of analog/IEC 61850 conversion units. IED Hardware tests inserted in a loop with activation by digital commands as well as by direct reading of amplified voltages and currents. Preparation/Elaboration of laboratory guides for testing different typical protection systems. Real-time simulation of centralized protection control (CPC) systems.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/813-Proj. SmartRetail– refª C6632206063-00466847

    Type of position: Research Grant (BI)
    Duration: 5 months
    Deadline to apply: 2025-12-16
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/813 under the scope of the Project SmartRetail– refª C6632206063-00466847, 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 goal of this project is to design and evaluate eventually consistent authentication mechanisms tailored for smart retail applications, where intermittent connectivity, edge deployments, and latency variability are commonplace.

    Modern smart retail platforms rely on cloud-hosted identity systems to authenticate both customers and store operators in scenarios such as mobile loyalty apps, RFID-tag scanning devices, self-checkout terminals, and in-store management dashboards. However, these authentication workflows typically require strong consistency: all identity components must be online simultaneously for login, verification, and credential update operations. This rigid requirement can lead to delays, login failures, and reduced usability during peak periods or in stores with unstable connectivity.

    This project explores a hybrid authentication model that allows certain operations to proceed under eventual consistency, while retaining strong consistency guarantees for critical operations such as credential revocation and fraud prevention.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/814-Proj. SmartRetail– refª C6632206063-00466847

    Type of position: Research Grant (BI)
    Duration: 5 months
    Deadline to apply: 2025-12-16
    Description

    ONE (1) research grant for students with MSc degree with reference number BI|2025/814 under the scope of the Project SmartRetail– refª C6632206063-00466847,  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 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 the susceptibility and mitigation of smart-retail network infrastructures to SYN flood attacks, a type of Distributed Denial of Service (DDoS) attacks that continue to grow in frequency and intensity, posing significant challenges to traditional mitigation methods due to their scale, diversity, and strain on network resources. Considering these attacks, this project has the following main goals: (1) Design and implement FloodKiller, a novel system that leverages the high-performance capabilities of programmable switches alongside the memory scalability made possible by RDMA. By offloading state-heavy data to RDMA-enabled external memory, FloodKiller aims to overcome the limitations of conventional defense mechanisms, enhancing scalability, accuracy, and reducing latency. (2) Develop specialized optimizations, including optimizing RDMA integration, developing efficient packet stalling methods during memory retrieval, and designing mechanisms for tracking verified connections and memory address mappings. (3) Evaluate FloodKiller's effectiveness using Tofino programmable switches. The expected outcome of this project includes a report of the analyzed solutions, a software prototype of the implemented solution, and a research paper.


    Contact email: bolsas@inesc-id.pt

  • BI|2025/802 Project ATE – Refª C644914747-0000023

    Type of position: Research Grant (BI)
    Duration: 5 months
    Deadline to apply: 2025-12-16
    Description

    ONE (1) research grant for students with BSc degree with reference number BI|2025/802 under the scope of the Project ATE – Refª C644914747-0000023 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 

    Definition and simulation of algorithms for detecting intermittent faults in compensated networks. Identification and testing of conditions for selective protection of intermittent faults in meshed and radial networks. Emulation with OPAL-RT of an IED with functionalities for detecting intermittent faults using analog/IEC 61850 conversion units. Real-time simulation in the OPAL-RT system of algorithms for detecting intermittent faults. Definition and measurement of effectiveness indicators for the tested algorithms.


    Contact email: bolsas@inesc-id.pt

Contract