Θέσεις Εργασίας

[ICS-2415] Call for expression of interest for two (2) positions for R&D Engineers with a degree in Computer Science or Computer Engineering
We seek two (2) recent graduate Research & Development Engineers with a degree in Computer Science or Computer Engineering for our team. The candidates will contribute to the R&D activities of FORTH in the context of the EC-funded project HIGHER, particularly in (i) development of low-level control firmware and system software, and (ii) validation and evaluation of use cases. The HIGHER project follows the Open Compute Project (OCP) Server family of standards to build processor modules for computation and acceleration, alongside a system security/control module. The project aims to build modular rack-scale systems, running with fully-featured operating systems and runtimes, and incorporating reusable standards-based infrastructure that encompasses hardware, low-level firmware, and systems software, while ensuring trustworthy functionality for managing, securing, and controlling servers. The project's open-source hardware and software outcomes will enhance European Digital Autonomy and facilitate wide adoption. Furthermore, the project will assemble representative software stacks supporting a range of use cases, including accelerated data processing and analysis for converged Cloud and HPC platforms, Infrastructure-as-a-Service with standardized management and monitoring, Platform-as-a-Service facilitating large-scale data processing for ML inference and data analytics, and memory pool management at the server rack level, with access control safeguards aligned with maturing CXL standards. Requirements • Diploma in Computer Science or Computer Engineering • Physical presence at FORTH, Heraklion, Crete for the duration of the position • Experience in system programming in Linux using the C language • Experience in Linux-based systems development and evaluation, with development boards and emulators • Fluent knowledge of English • Names of at least three professional references • Willingness and ability to work cooperatively within a team, to learn, and to adapt to the projects
Laboratory: CARV
Date of announcement: 12-11-2025
Closing date: 24-11-2025, 16:00
More info (english version)
apply for the position...
[ICS-2414] Call for expression of interest for one (1) position of Researcher with a Ph.D. degree in Computer Science or a related Engineering field
We seek one researcher with a Ph.D. in Computer Science or a related Engineering field. The candidate will participate in the R&D activities of FORTH-ICS in the context of the H2020 project “MAGICIAN - iMmersive leArninG for ImperfeCtion detectIon and repAir through human-robot interactioN”, funded under Horizon 2020, HORIZON-CL4-2022-DIGITAL-EMERGING-02, and will work on Computer Vision related aspects. A common trait of many important markets is the increasing attention of consumers to the aesthetic quality of the products. Even products like mid-segment cars are required to be defect-free in all the areas falling under the direct sight of the customer. These expectations translate into high-quality standards in the production process, which are currently met by requiring an important physical effort to the workers in unsafe environments. The MAGICIAN project will take on the challenge producing a modular automation solution in which robots are used to detect and rework production defects before the last production phases commence and the aesthetics of the product is finalized. The project will produce two robotic solutions, one for defect analysis (the SR) and one for the defects’ rework (the CR). The SR and the CR can be used separately, with the humans remaining in charge of some of the activities, or in combination, with the CR operating on the defects identified by the SR. The SR can also be used in connection with the welding robotic station in order to adapt the process parameters. The robots will use Artificial Intelligence modules to detect and discriminate the defects from multi-modal data (the SR) or to decide the best policy to use for defect rework (the CR). In both cases, the decision logic of the modules will be trained using machine learning algorithms. The training data set will be acquired with the help of workers, who will operate on semiworked products within a controlled environment. The SR and the CR will rely on the software services of a common robotic platform. The solution will be developed adopting a human-centered approach, which will allow us to evaluate the impact of the innovation on the production processes and remove the most important asperities along this path. The effectiveness of the solution will be tested on a usecase, and its generality proven by recruiting additional contributors and use-cases through a FSTP scheme.
Laboratory: CVRL
Date of announcement: 12-11-2025
Closing date: 24-11-2025, 16:00
More info (english version)
apply for the position...
[ICS-2413] Call for expression of interest for one (1) position of Researcher with a Ph.D. degree in Computer Science or a related Engineering field
We seek one researcher with a Ph.D. in Computer Science or a related Engineering field. The candidate will participate in the R&D activities of FORTH-ICS in the context of the H2020 project “MAGICIAN - iMmersive leArninG for ImperfeCtion detectIon and repAir through human-robot interactioN”, funded under Horizon 2020, HORIZON-CL4-2022-DIGITAL-EMERGING-02, and will work on Computer Vision related aspects.A common trait of many important markets is the increasing attention of consumers to the aesthetic quality of the products. Even products like mid-segment cars are required to be defect-free in all the areas falling under the direct sight of the customer. These expectations translate into high-quality standards in the production process, which are currently met by requiring an important physical effort to the workers in unsafe environments. The MAGICIAN project will take on the challenge producing a modular automation solution in which robots are used to detect and rework production defects before the last production phases commence and the aesthetics of the product is finalized. The project will produce two robotic solutions, one for defect analysis (the SR) and one for the defects’ rework (the CR). The SR and the CR can be used separately, with the humans remaining in charge of some of the activities, or in combination, with the CR operating on the defects identified by the SR. The SR can also be used in connection with the welding robotic station in order to adapt the process parameters. The robots will use Artificial Intelligence modules to detect and discriminate the defects from multi-modal data (the SR) or to decide the best policy to use for defect rework (the CR). In both cases, the decision logic of the modules will be trained using machine learning algorithms. The training data set will be acquired with the help of workers, who will operate on semiworked products within a controlled environment. The SR and the CR will rely on the software services of a common robotic platform. The solution will be developed adopting a human-centered approach, which will allow us to evaluate the impact of the innovation on the production processes and remove the most important asperities along this path. The effectiveness of the solution will be tested on a usecase, and its generality proven by recruiting additional contributors and use-cases through a FSTP scheme.
Laboratory: CVRL
Date of announcement: 12-11-2025
Closing date: 24-11-2025, 16:00
More info (english version)
apply for the position...

Archive

[ICS-2407] Call for expression of interest for one (1) position, for one experienced researcher (PhD holder) in Computer Science or Engineering
We seek one experienced researcher (PhD holder) in Computer Science or Engineering with a strong background in AI, simulation systems, and decision support technologies, to join the SEAVISTA project – Strategic Enhanced Maritime Awareness for Integrated Security and Decision Support – funded under the FRONTEX RESEARCH GRANTS PROGRAMME, PROCEDURE 2024/CFP/INNOVATE/01. SEAVISTA aims to develop an AI-driven, event-based decision support toolbox for maritime border surveillance. The system integrates multi-source sensory data, predictive analytics, and physics-informed 3D simulation for real-time and offline threat detection, anomaly analysis, and asset deployment optimization. The candidate will lead research on AI-driven decision support for maritime border surveillance using physics-informed simulation, multi-source data fusion, and explainable machine learning. Specifically: • AI-based maritime threat detection, predictive models, and optimization methods • Integration of simulation with multi-modal data (AIS, radar, satellite, environmental) • Development of evaluation methodologies and explainable AI pipelines • Coordination of experimentation and validation tasks at TRL 5–6
Laboratory: CVRL
Date of announcement: 20-10-2025
Closing date: 31-10-2025, 16:00
More info (english version)
Available Results :
Results
DIAVGEIA Search Number: (https://diavgeia.gov.gr with ADA: 9ΜΕ9469ΗΚΥ-ΓΡΥ)
[ICS-2406] Call for expression of interest for one (1) position for one MSc student in Computer Science or Computer Engineering or Electrical Engineering
We seek one MSc student in Computer Science or Computer Engineering or Electrical Engineering to support the implementation and testing of software components in the context of the SEAVISTA project – Strategic Enhanced Maritime Awareness for Integrated Security and Decision Support – funded under the FRONTEX Research Grants Programme (2024/CFP/INNOVATE/01). The job scope is AI-driven decision support for maritime border surveillance using physics-informed simulation, multi-source data fusion, and explainable machine learning. The selected candidate will assist in the integration and testing of AI models, data pipelines, and simulation tools, helping bridge the gap between research prototypes and robust demonstrators for maritime situational awareness. Specifically, the job’s main responsibilities are: • Develop and maintain code for data preprocessing, pipelines, and interfaces • Implement prototype features within simulation and analytics components • Conduct testing and validation of AI-based subsystems • Support documentation and demos for project deliverables
Laboratory: CVRL
Date of announcement: 20-10-2025
Closing date: 31-10-2025, 16:00
More info (english version)
Available Results :
Results
DIAVGEIA Search Number: (https://diavgeia.gov.gr with ADA: ΡΥΩ6469ΗΚΥ-Τ5Α)
[ICS-2405] Call for expression of interest for one (1) position of Computer Scientist or Engineer, MSc holder
We seek one Computer Scientist or Engineer (MSc holder) with a background in machine learning and data fusion, to join the SEAVISTA project – Strategic Enhanced Maritime Awareness for Integrated Security and Decision Support – funded under the FRONTEX Research Grants Programme (2024/CFP/INNOVATE/01).The scope of the position is AI-driven decision support for maritime border surveillance using physics-informed simulation, multi-source data fusion, and explainable machine learning. The selected candidate will contribute to the development of AI-based models for anomaly detection, behavior classification, and real-time risk assessment in maritime environments. The position involves working with diverse data sources (e.g., AIS, radar, satellite) and supporting the integration of these capabilities into the SEAVISTA simulation and decision support platform.
Laboratory: CVRL
Date of announcement: 20-10-2025
Closing date: 31-10-2025, 16:00
More info (english version)
Available Results :
Results
DIAVGEIA Search Number: (https://diavgeia.gov.gr with ADA: ΡΓΗΑ469ΗΚΥ-ΖΛΕ)
[ICS-2404] Call for expression of interest for one (1) position, for a Computer Scientist or Engineer
We seek one experienced member for our team, one Computer Scientist or Engineer, with background in European and/or National ICT RTD projects, to contribute to the research and development activities of the COLOURS - Collaborative On-cloud Lab for the conservation and digital restoration of ColOUred heritage collectionS project (Grant Agreement number: 101233413), funded under HORIZON-CL2-2024-HERITAGE-ECCCH-01-05.Preserving Europe’s cultural heritage requires advanced digital tools that enable seamless collaboration among curators, conservators, and scientists. These tools must preserve primary data referenced to digital representations and twins and maintain documentation of analysis and reasoning processes. They must also preserve “raw” primary data to ensure accuracy and integrity and support future analysis techniques as the methods evolve. Colour, a key element of cultural heritage, is critical to understanding the historical and artistic significance of artefacts. However, its preservation faces challenges such as fading, alteration or loss. Events like the Notre Dame fire highlight the need for adaptive collaborative environments, while public reaction to the Sistine Chapel restoration highlights the importance of tools that predict and communicate restoration results. Building on 2 years of research and development conducted under PERCEIVE, the project aims to make a major contribution to the digital transition of cultural heritage conservation and restoration by developing integrated colour analysis and restoration tools tailored to diverse artefacts, including polychrome sculptures, paintings, textiles, historic films and photographs. These tools, fully interoperable with the European Collaborative Cloud for Cultural Heritage, will provide high-precision analysis, simulate restoration results with perceptual accuracy, and support interdisciplinary collaboration through hybrid spaces that merge virtual and physical environments. These spaces will enable real-time interaction with the digital twins , fostering inclusive decision-making among conservators, curators, and scientists, while ensuring accessibility for remote participants. In addition, the project seeks to enhance public engagement by leveraging mixed reality technologies and digital storytelling to showcase restored colours and convey the authenticity of artefacts, promoting a deeper appreciation of CH.
Laboratory: CVRL
Date of announcement: 20-10-2025
Closing date: 31-10-2025, 16:00
More info (english version)
Available Results :
Results
DIAVGEIA Search Number: (https://diavgeia.gov.gr with ADA: 96ΥΖ469ΗΚΥ-ΖΒ7)
[ICS-2403] Call for expression of interest for one (1) position of student enrolled to a University MSc Program in Computer Science or Computer Engineering or Electrical Engineering
We seek one (1) student enrolled to a University MSc Program in Computer Science or Computer Engineering or Electrical Engineering. The candidate will participate in the R&D activities of FORTH in the context of the EuroHPC JU-funded project NET4EXA. The NET4EXA project aims to create an advanced interconnect, which will scale to hundreds of thousands of computing nodes and will support modern HPC systems that are designed for massive AI tasks, such as the training of Large Language Models. The interconnect forms the backbone of such systems, and their overall performance is intimately tied to the scalability of the network and its tight coupling with the high-end compute elements Requirements • Enrolled to a University graduate MSc Program in Computer Science or Computer Engineering • Physical presence at FORTH, Heraklion, Crete for the duration of the position • Demonstrated experience with the C language. • Demonstrated knowledge with the runtime environment and compilations tools for HPC accelerators, such as NVIDIA GPU’s. • Demonstrated knowledge with workload-driven evaluation of GPU accelerators using AI frameworks, such a PyTorch or TensorFlow. • Demonstrated experience with communication protocols and abstractions for high-speed interconnects that provide RDMA-based operations. • Fluent knowledge of English. • Names of at least three professional references
Laboratory: CARV
Date of announcement: 08-10-2025
Closing date: 20-10-2025, 16:00
More info (english version)
Available Results :
Results
DIAVGEIA Search Number: (https://diavgeia.gov.gr with ADA: 9ΣΗΕ469ΗΚΥ-ΝΨ7)

Pages

Ολες οι παλαιότερες προκυρήξεις