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Supporting EOSC
Co-funded by the European Union
Co-funded by UKRI

Fellowship Programme

Introducing the Skills4EOSC Fellowship Programme: Unlocking Opportunities in Open Science and FAIR Data

Are you a data professional with a passion for Open Science, FAIR data, and research data management practices? Are you eager to enhance your skills and collaborate with professionals from different institutions?

The Skills4EOSC project launched its Fellowship Programme, a unique opportunity for data professionals in Open Science to embark on a transformative journey.

Updates on the Fellowship Programme

February 29, 2024 - The deadline for submissions to the Skills4EOSC Fellowship Programme has been extended until March 17th

December 21, 2023 - Launch of the second call for the Fellowship Programme: You can submit your application by February 29, 2024, following the instructions provided below.

November 29, 2023 - We are currently assessing the first round of applications, and the second round is expected to open around mid-December, following the notification of the first round assessment results.

About the Fellowship Programme

The modern research landscape demands that research-performing organisation foster and sustain professional profiles dedicated to Open Science, FAIR data principles, and data management practices. The Skills4EOSC Fellowship Programme aims to address this need by sponsoring short secondments for data professionals in Open Science. This initiative is tailored for data stewards and individuals engaged in data support related to Open Science, collectively referred to as "Fellows" hereinafter.

The programme seeks to stimulate life-long learning through knowledge and experience exchange between data professionals across different institutions, fostering collaboration and facilitating participation in relevant professional networks.

Aims of the Fellowship

The Skills4EOSC Fellowship Programme has four primary objectives:

  1. Support Life-Long Learning: Encourage data professionals in Open Science to acquire skills relevant to Open and FAIR data practices and research data management, fostering continuous professional growth.
  2. Institutional Capacity Building: Empower Fellows to build or consolidate Open and FAIR data practices within their home institutions, driving positive organisational change.
  3. Knowledge Exchange: Enable Fellows to explore, establish, and share services, tools, and infrastructures related to Open and FAIR data.
  4. Strengthen Collaboration: Facilitate collaboration among institutions by encouraging participation in relevant professional networks, creating a vibrant community of data professionals.

Types of Fellowships

The Skills4EOSC Fellowship Programme offers three distinct forms of fellowships:

  1. Project Proposed by the Fellow: Fellows can propose a project that aligns with the objectives and expertise of the host institution. This approach allows for focused collaboration, ensuring impactful outcomes.
  2. Joining a Host Institution's Project: Alternatively, Fellows may join an existing project proposed by the host institution, leveraging their skills and knowledge to advance ongoing initiatives.
  3. Internship in Research Data Support: Fellows can participate in an internship, actively engaging in day-to-day activities related to research data support. This immersive experience offers a comprehensive understanding of research data management practices within the host institution.

Regardless of the chosen form, the fellowship must enhance or benefit the Fellow's career and current role.

Duration and Eligibility

The duration of the fellowship can be one, two, or three months, and Fellows must take up their placements no later than one year after acceptance.

The Skills4EOSC Fellowship Programme is open to all data professionals in Open Science, including data stewards and other individuals involved in data support. Early career professionals are especially encouraged to apply. To be eligible, applicants must be affiliated with a publicly funded research-performing organisation in an EU or EU-widening country and must comply with the mobility rule.

Application Process

Applicants must use the provided templates for their application, budget, and CV. Additionally, they must include a letter of support from their home institution and a letter of invitation from the host institution.

Host Institutions

Please contact individual institutions directly to find out more about their RDM support and Open Science services and to plan your fellowship proposal prior to submitting your application.

For the first call and the second call, the host institutions are as follows:

  • Polytechnic University of Turin (POLITO)

    Polytechnic University of Turin (POLITO)

    Politecnico di Torino recognizes the fundamental role of data produced during research activities for scientific and technological progress. Therefore, it recognizes the importance of a correct and responsible RDM for maintaining the values of quality and integrity of scientific research. For this reason Politecnico di Torino is committed to applying the highest standards for the collection, storage, preservation and sharing of data and software. Fellows at Politecnico di Torino could work on one of the following projects/activities:

    • FAIR by designs workflows. Work in direct contact with researchers in a specific domain of interest to develop workflows and projects designed to follow the FAIR principles since the very beginning. The chosen research group will depend on the fellow background.
    • FAIR software platform. Contribute to the project of the Politecnico di Torino aiming at the development of an institutional platform for software management, versioning, protection and integration with Software Heritage.
    • DMP templates customization and DMP evaluation guidelines: creation of new DMP templates for different scientific domains and creation of a guide for DMPs evaluation.

    Information for applicants: Please contact POLITO to find out more about their plans for the fellowship

    Contact: Mauro Paschetta, This email address is being protected from spambots. You need JavaScript enabled to view it.

  • Italian Institute of Technology (IIT)

    Italian Institute of Technology (IIT)

    Following international guidelines and inspired by values of reproducibility and efficiency, IIT recognizes the importance of managing research data in a responsible way. Research Data Management (RDM) has been a priority for IIT since 2018, when dedicated resources were invested to create support services for scientists. In parallel, IIT has sustained Open Science practices, as a means to promote dissemination of IIT results, to increase knowledge transfer, and to stimulate trust in Science and Technology, also with an educational and societal commitment.

    RDM support at IIT covers the following areas:

    Planning research.
    IIT provides professional support to its scientists in creating data management plans (DMPs), including guidelines and tailored templates. A support working group for DMP writing has been created, involving IT, legal, technology transfer professionals, and data curators.

    Working with data.
    IIT has adopted an Information Security Policy that guides researchers in data protection depending on the risk classification. IIT provides IT and legal support to researchers for the correct management of personal and high-risk data, as well as tailored storage and backup solutions for different volumes and types of data.

    Publishing and preserving.
    IIT has set up its own institutional research data repository, IIT Dataverse, which allows data to be shared according to the FAIR principles, cited, and linked to scientific articles by assigning digital persistent identifiers. IIT Dataverse is one of the first Italian instances of Dataverse, is catalogued in, and integrated with OpenAIRE Explore. RDM support has produced several guidelines and procedures to help researchers use IIT Dataverse and other repositories.

    Fellows at IIT could work on one of the following projects/activities, all aimed at improving the current RDM service:

    • Custom DMP templates for disciplines: Extend existing or create new templates for different disciplinary contexts, optionally using tools like Data Stewardship Wizard or DMPOnline.
    • Piloting data FAIRification: Collaborate with researchers in a selected domain of interest to develop workflows and procedures for the collection of metadata and documentation thus enabling FAIR data production.
    • Integrate Dataverse with externally controlled vocabularies: Extend metadata schemas available in IIT Dataverse to support different disciplines and integrate it with externally controlled vocabularies using available features.

  • University of Trento (UNITN)

    University of Trento (UNITN)

    Information for applicants: UNITN is developing training material for their researchers on FAIR data, data quality and promotion and valorisation of datasets. Confirmed duration of placement is one month, as approved by the head of the research directorate. Please contact us to find out more.

    Research Data Support at UINTN
    UNITN Open Science Policy

    Contact: Dr Vincenzo Maltese, This email address is being protected from spambots. You need JavaScript enabled to view it.

  • Euro‑Mediterranean Center on Climate Change (CMCC)

    Euro‑Mediterranean Center on Climate Change (CMCC)

    CMCC will offer the option to join an ongoing project, in which the fellow will be committed to supporting the ASC division project activities, ranging from the optimization of climate models to the design and implementation of Data science solutions. In addition, the candidates might be involved in the design and development of ML/AI techniques applied to climate change. More relevant details will be worked out with the candidate according to their qualifications and interests. Projects at CMCC would suit candidates with some of the following qualifications and experience:

    • M.Sc. degree in Computer science or computer engineering
    • Expertise in programming (Python or FORTRAN)
    • Expertise in database design
    • Expertise in sensor network
    • Preferred knowledge in parallel programming
    • Preferred knowledge in climate data analytics
    • Preferred knowledge in edge computing

    CMCC Advanced Scientific Computing Division

    Contact: Fabrizio Antonio, This email address is being protected from spambots. You need JavaScript enabled to view it.

  • 4TU.ResearchData


    A fellowship at 4TU.ResearchData can take the form of joining an ongoing project, an internship working across different teams for example with the repository or community team, or a candidate can propose a project of their own, which aligns with the goals and activities of 4TU.ResearchData. The placement will last for three months. The fellow can expect to advance their knowledge of FAIR data and open science within science, engineering and design disciplines. They will understand how large research-intensive organisations operate within the Netherlands, become familiar with the national (Dutch) and international landscape on open science and FAIR Data and build personal and professional networks within their area of work/interest.

    There is currently one project that a fellow could join:

    Support the Data and Software Academy project
    The fellow will support the development of the courses for the Data and Software Academy pilot in collaboration with a national team of Research Data Management specialists, fellows and staff members of 4TU.ResearchData. According to the period, the fellow will join us, they will contribute to a phase: developing a workshop for students (in the field of data and software interoperability), helping with running the workshop and supporting the students with their projects, collecting feedback and prepare a report about the course.


    Please contact us to plan your proposal.
    Contact: Madeleine de Smaele, This email address is being protected from spambots. You need JavaScript enabled to view it.

  • TU Delft

    TU Delft

    The fellow will work on a new or ongoing project proposed by the TU Delft Research Data and Software service. The project aims to improve services around research data and software management, and/or Data Stewardship.

    The placement at TU Delft will last for 1-3 months. During the project, the fellow will collaborate with various stakeholders including researchers, Data Stewards, Data Managers, RSEs, RDM trainers, and other research services.

    Please contact TU Delft to explore options for your proposal.

    TU Delft RDM services:
    Contact person: Yan Wang This email address is being protected from spambots. You need JavaScript enabled to view it.

  • Aarhus University (AU)

    Aarhus University (AU)

    Research Data Management at AU Library
    Open Science at AU Library

    Please contact AU to find out more about their plans for the fellowship
    Contact: Birte Christensen-Dalsgaard, This email address is being protected from spambots. You need JavaScript enabled to view it. [CS1]

  • Karlsruhe Institute of Technology (KIT)

    Karlsruhe Institute of Technology (KIT)

    The Karlsruhe Institute of Technology (KIT) is “The Research University in the Helmholtz Association.” As the only German university of excellence with a national large-scale research sector, KIT offers students, researchers, and employees unique learning, teaching, and working conditions. Presently, more than 9000 people are working at KIT, of which more than half are conducting research in a broad range of disciplines from natural sciences to engineering, to economics, to the humanities and social sciences. This makes KIT one of the largest science institutions in Europe.

    Good research today must not only be rigorous, innovative and insightful - it also relies on good research data management. Therefore, the support team RDM@KIT promotes the topic of research data management at KIT. In the support team RDM@KIT, different service units of KIT cooperate across institutes. The main responsibility of the support team lies at the KIT Library and the Steinbuch Centre for Computing. Within the research services department of the KIT Library, you will be part of a friendly team of 15 people with heterogeneous study backgrounds working on many third-party-funded projects, in a collegial working atmosphere and an attractive working environment.

    The Skills4EOSC Fellowship Programme at KIT provides insights into the daily work of the support team. This includes, among others, the involvement in the international registry of research data repositories re3data working group, the involvement in the KIT-internal repository for research data RADAR4KIT and the participation in specific open science projects. The Fellowship Programme provides an outstanding opportunity to network and exchange experiences with local data professionals and scientists.

    Skills4EOSC collaborates with the third-party funded project bwFDM in the development of a certificate course on RDM. The aim of this course is to facilitate the training of data professionals at KIT and beyond. The Skills4EOSC Fellowship Programme at KIT includes the development of this course, which may involve but is not limited to, contributing conceptional input for the preparation of a course module or assisting in the implementation of a Train-the-Trainer concept on RDM. Tasks are carried out in close collaboration with members of the project teams.

    We are looking forward to your application for a two to three-month stay with us. If you have questions or ideas regarding the Fellowship Programme, please do not hesitate to contact us.

    Karlsruhe Institute of Technology (KIT)

    Contact: Claudia Kramer, This email address is being protected from spambots. You need JavaScript enabled to view it.

  • KU Leuven (KUL)

    KU Leuven (KUL)

    The fellow will be in close contact with research support staff of KU Leuven Libraries who are located across KU Leuven campuses and specifically those who provide research data support. This support is coordinated through the RDM Competence Centre (RDM-CC), a virtual collaboration across the ICT department, research coordination office and KU Leuven Libraries. Depending on the project or internship, the fellow thus has the opportunity to focus on more operational research data support (e.g. 1st or 2ndlevel support, participation in the organisation of training sessions or giving advice to researchers) or participate in one of the RDM-CC actions or projects with a broader scope or target.

    KUL Research Data Management
    KUL Open Science
    Research Support at KUL Libraries

    Contact: Johan Philips, This email address is being protected from spambots. You need JavaScript enabled to view it.

  • Chalmers University of Technology (Chalmers)

    Chalmers University of Technology (Chalmers)

    Information for applicants: Chalmers suggests projects aligning with the following themes
    These projects could also lead to a collaborative paper after the fellowship period if the fellow is interested:

    • Reviewing and summarising Swedish and European funding agencies’ requirements for ‘trusted’ data repositories and the definitions of and requirements for trust in this context.
    • Developing, together with Chalmers e-Commons, a new Data Management Plan model for Data Stewardship Wizard which can be used to fulfil multiple funding requirements/recommendations for DMPs. This project would require a good amount of collaboration with the rest of the data management team at Chalmers.
    • Developing, together with Chalmers e-Commons, new training material to be used in research data management training. Knowledge of the Carpentries framework can be meritable.
    • Develop a method to identify and harvest information from data availability statements in academic publications
    • Identify barriers to research collaboration between private actors and Chalmers and/or organizations in multiple countries, with a focus on data sharing.

    The host infrastructure will be Chalmers e-Commons, Chalmers’ gateway to a collection of local, national, and international digital expert functions and resources. Researchers, research groups and research infrastructures at Chalmers can turn to e-Commons for support in making large-scale computing calculations/analyses, applying AI and Machine Learning in research and managing research data throughout its life cycle. Chalmers Data Office is a group within e-Commons specifically dealing with Research Data Management.

    Chalmers e-Commons

    Contact: Jeremy Azzopardi, This email address is being protected from spambots. You need JavaScript enabled to view it.

Fellowship Commitments

Fellows will be required to participate in a final survey to provide feedback about their fellowship experience. Additionally, they will need to submit a report detailing the skills and capabilities gained during the programme and offer suggestions for improvement, if any. This report is due by one month following the end of the fellowship.

For further information, please send an email to This email address is being protected from spambots. You need JavaScript enabled to view it.