Research Associate (Doctoral Researcher) (f/m/d) / EG 13 TV-L in the fields of data science and research data management

At the University of Bremen, the Digital Media Lab is seeking for the BMBF project "DataNord" a full-time position for the BMBF-project “DataNord” for a period of 3 years starting as soon as possible:

Research Associate (Doctoral Researcher) (f/m/d) / EG 13 TV-L in the fields of data science and research data management

The Digital Media Lab conducts research in the field of research data management within the application area of materials science. Further research topics are Human-centred AI and Human-Computer Interaction.

The applicant (f/m/d) has the opportunity to acquire further qualifications in these areas of expertise with the aim of completing a doctorate.

The employment is fixed-term and governed by the Act of Academic Fixed-Term Contract, §2 1 (Wissenschaftszeitvertragsgesetz – WissZeitVG). Therefore, candidates may only be considered for appointment if they still have the respective qualification periods available in accordance with § 2 (1) WissZeitVG.

Background

The position is part of the collaborative BMBF project “DataNord” that aims at establishing an interdisciplinary data competence center for the Bremen region. In DataNord, members of the U Bremen Research Alliance – the cooperative network of the University of Bremen and twelve non-university research institutes – work together with other regional institutions. The DataNord team will consist of 15 people who are distributed among the partner institutions and will work closely together. The position advertised here is part of one of five research projects of the "DataNord Research Academy" and will be carried out in close collaboration with the Fraunhofer Institute for Manufacturing Technology and Advanced Materials (IFAM). A close collaboration with the other project members is planned.

Job Description

The successful candidate will conduct research in research data management and generate "in silico" data from laboratory experiments using machine learning methods. By generating this type of synthetic data, new data sets can be produced and gaps in existing data sets can be filled post hoc. In addition, an explanatory component is to be developed and empirically analyzed which, in the sense of explainable AI (XAI), helps the users of synthetic data sets to understand why these results were obtained and how.

Qualification

• completed scientific university studies (Master's or diploma degree) in computer science / digital media or related fields

• Expertise in machine learning

• Commitment to interdisciplinary, team-based research

• very good written and spoken English skills

• Interest in materials science and research data

• Knowledge in one or more of the following areas:

• Machine learning

• Explainable AI

• Open data and open science

We offer you the opportunity to work as part of an interdisciplinary and dedicated team on innovative topics and to actively shape the data culture of tomorrow. The job tasks are diverse, the working atmosphere is open, and there is the opportunity to regularly participate in further trainings. The research-oriented and dynamic environment of the DataNord network offers exciting projects and excellent opportunities for networking with other disciplines and institutions. At the University of Bremen, you will work in an inspiring and family-friendly environment (including on-site daycare facilities) with flexible working hours. You will have a modern, well-equipped workplace. Mobile working is possible.

General information

The university is family-friendly, diverse and sees itself as an international university. We therefore welcome all applicants regardless of gender, nationality, ethnic and social origin, religion/belief, disability, age, sexual orientation and identity.

The University of Bremen strives to increase the proportion of women on the academic staff and therefore strongly encourages qualified women to apply.

Please send any questions about the position and your application with the reference number A265/23 by 07.02.2024 to:

Prof. Dr Rainer Malaka

Digital Media Lab

University of Bremen

28334 Bremen / Germany

or as one single PDF file by unencrypted electronic mail to: dm-sekrprotect me ?!tziprotect me ?!.de

If you are sending a paper application, please ensure that you only send copies of documents, as all application documents received will be destroyed after the selection procedure.

Any costs for the application cannot be reimbursed.