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DRIVEN guides all elements of doctoral training and career development through achieving research excellence, supporting its Doctoral Candidates to become creative, critical and autonomous intellectual risk takers, with the potential ability and confidence to push the boundaries of scientific knowledge. Our attractive, supportive environment as institutions, teams and individuals will empower them to take responsibility for the scope, direction and progress of their research project. DRIVEN’s conceptual approach is based on interdisciplinarity, which is continued and intensified at the doctoral training level. The scientific network of the Principal Investigators provides rich options for the Doctoral Candidate’s later exposure to industry, public institutions or other potential employment sectors as well as access to a range of international scientific communities and mobility opportunities.

DRIVEN is integrated into the existing doctoral education and training environments at the involved faculties of the University of Luxembourg. Our DTU is an integral part of the transversal Doctoral Programme in Computational Sciences, organised across the Doctoral School in Science and Engineering (DSSE) at the Faculty of Science, Technology and Communication (FSTC), the Doctoral School in Humanities and Social Sciences (DSHSS) at the Faculty of Language and Literature, Humanities, Arts and Education (FLSHASE) and the Doctoral School in Economics and Finance (DSEF) at the Faculty of Law, Economics and Finance (FDEF). This structure provides the necessary framework to develop DRIVEN’s innovative doctoral training strategies.


Each DC has his/her individual thematic and scientific background, so a different set of skills might already be available or missing. More importantly, he/she brings his/her own ideas of approaching and developing the research project in data-driven science. Therefore, DCs – together with their supervisors – will establish a Doctoral Education Agreement (DEA) within the first 3 months of the doctorate. In this individual training plan, aspects and instruments of the DC’s personal development shall be identified. This contains a reflection on the candidate’s and supervisor’s expectations, critical stock-taking of the present intellectual skills (analytical and synthetic thinking, creativity, intellectual risk taking), academic skills (managing complexity and uncertainty, scholarly networking, working in a high-level research environment, exchange and transfer of knowledge, ethical principles) and personal skills (project management, communication, teamwork, leadership, teaching, event organisation, dissemination to experts and non-experts), and evaluating the DC’s strengths and weaknesses in scientific knowledge and technical abilities. From these observations, long and short-term objectives for individualised training and development to overcome critical gaps shall be formulated and suitable measures of formal research training – direct or structured (see below) – are selected as a joint effort shared between the candidate and the supervisor. In addition, supplementary training opportunities shall be taken into account: e.g. planning the dissemination of results and the doctoral thesis, participation and contribution to research collaborations, outgoing activities (mobility) and teaching (light loads). In a later phase of the doctorate, the DEA shall also include elements of professional development to prepare the candidate for an academic or non-academic career, depending on his/her preferences and intentions. Supervisors in DRIVEN continuously monitor the progress of the DCs according to the DEA and review the agreement with them every 12 months. The DEA is documented and its fulfilment part of reporting activity of the Thesis Supervisory Committee (CET).

Training through direct interaction

A key concept of DRIVEN is to provide scientific advice and guidance during the execution of doctoral research through an interdisciplinary team of supervisors. While each DC will have his/her main supervisor, at least one other PI of the DTU (preferably from a different thematic cluster) will continuously co-supervise the project together with other (internal or external) advisors that form the CET. Our supervisors ensure regular and high-quality direct interaction with the candidate and organise his/her social and scientific immersion in the research team(s), fostering transfer of day-to-day research competence through interaction with the research teams.

Training through structured activity.

DRIVEN doctoral candidates are required to participate in structured training activities that contribute to their scientific and personal development. Eligible training activities are associated with one of the following categories mentioned below. Structured training activities are planned and agreed on by the DC, the supervisor and the members of the CET. Upon successful participation, credit points are obtained by the candidate. Over the course of the PhD research mission, a minimum of 20 ECTS (equivalent to 500 hours) must be verified.

Category 1 – Fundamental and advanced scientific competences, thematic training 

Activities targeting core methodological competences constitute the vertical axis of thematic training in DRIVEN. A set of mandatory courses and tutorials will provide the DC with the necessary scientific and more technical foundations in key enabling domains for data-driven discovery, e.g. Applied Mathematics, Numerical Methods, Statistical Analysis, Machine Learning Basics, Advanced Programming Skills, Computational Research and Development Environments, Software Engineering, Data Science and Visualisation. The elements of this DRIVEN training category enable DCs of heterogeneous scientific background to base their future research activities on a common theoretical basis and basic technological skills that will allow them to make progress quickly. As a guiding principle, lecture-format contact is used only sparingly, instead promoting the idea of “learning by doing research”.

Category 2 – Inter/cross-disciplinary competences, common academic and scientific modules

The horizontal axis of inter/cross-disciplinary training takes advantage of the multidisciplinary setting in DRIVEN. Seminars with hands-on sessions will introduce the DCs to the various research fields represented by the involved clusters and the associated domain-specific aspects of data availability, data characteristics, classical modelling and data-driven modelling approaches using demos and/or application templates. The elements of this DRIVEN training category will exemplify to the DCs aspects of data assimilation, data analysis and data-based discovery using a variety of showcase scenarios close to the scientific fields of the ongoing DTU research projects and therefore support transfer of knowledge to potentially very different disciplines or application domains through the shared similarity in the methodological core. It is expected that this approach equips the DCs with the necessary confidence for taking over leadership in their later professional activities.

Category 3 – Transferable skills training and development

The Office of the Vice-President for Doctoral Education and Training, International Relations and Gender at UL offers a wide range of centrally organised Transferable Skills Courses (TSC), including Time and Priority Management, Scientific Integrity, Presentation Skills, Lecturing Training, Intellectual Property, Knowledge Transfer and Social Media for Researchers, and provides counselling for professional development and career orientation (Campus Carrières). In addition, the faculties sponsor a series of initial and continuing professional development (CPD) workshops, and activities on teaching and learning in higher education. Candidates can develop their teaching and learning support skills as well as language skills (ULLC). DRIVEN will provide dedicated offers specifically addressing data ethics as well as the data dimension of Open Science and Entrepreneurship.