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DEDS
DEDS
Bruxelles, Belgium

DEDS

Data is a key asset in modern society. Data Science, which focuses on deriving valuable insight and knowledge from raw data, is indispensable for any economic, governmental, and scientific activity. Data Engineering provides the data ecosystem (i.e., data management pipelines, tools and services) that makes Data Science possible. The European Joint Doctorate in "Data Engineering for Data Science" (DEDS) is designed to develop education, research, and innovation at the intersection of Data Science and Data Engineering. Its core objective is to provide holistic support for the end-to-end management of the full lifecycle of data, from capture to exploitation by data scientists.

DEDS  operates under the Horizon 2020 - Marie Skłodowska-Curie Innovative Training Networks (H2020-MSCA-ITN-2020) framework. It is jointly organised by Université Libre de Bruxelles (Belgium), Universitat Politècnica de Catalunya (Spain), Aalborg Universitet (Denmark), and the Athena Research and Innovation Centre (Greece). Partner organisations from research, industry and the public sector prominently contribute to the programme by training students and providing secondments in a wide range of domains including Energy, Finance, Health, Transport, and Customer Relationship and Support.

DEDS is a 3-year doctoral programme based on a co-tutelle model. A complementary set of 15 joint, fully funded, doctoral projects focus on the main aspects of holistic management of the full data lifecycle. Each doctoral project is co-supervised by two beneficiaries and includes a secondment in a partner organisation, which grounds the research in practice and validate the proposed solutions. DEDS delivers innovative training comprising technical and transversal courses, four jointly organized summer and winter schools, as well as dissemination activities including open science events and a final conference. Upon graduation, a joint degree from the universities of the co-tutelle will be awarded.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 955895.