Postdoc & PhD 4 Learning Analytics, Frankfurt, Germany

The German Institute for International Educational Research (DIPF) is a national centre for educational research and educational information, it is jointly funded by the federal government and the federal states. DIPF is a member of the Leibniz Association operating from locations in Frankfurt am Main and Berlin, with around 300 employees.

We are currently building up an Educational Technology research group with a specific focus on Learning Analytics in Frankfurt Germany under close collaboration of the German Institute for International Education Research (DIPF) and the Computer Science faculty of the Goethe University of Frankfurt. Learning analytics is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs. A related field is educational data mining. Within our international research projects, we conduct learning analytics studies in higher education and schools.

The Information center for Education is seeking for

1 Postdoc in Data Science – Learning Analytics (full-time, for 4 years, EG 14 TV-H*)
2 PhD in Data Science – Learning Analytics (full-time, for 3 years, EG 13 TV-H*)

for its location in Frankfurt am Main.

The selected candidates need to explore and analyze datasets from learning management systems, assessment systems but also ubiquitous tracking devices such as wearables, cameras or beacons. The selected candidates should either be able to apply information retrieval or data mining techniques like RapidMiner, Weka, R or Python, or be able to visualize the findings from data mining with visualization frameworks as D3.js. We also welcome candidates with experiences in text mining technologies. A strong statistics background and the willingness to build up programming skills in one of the above-mentioned tools are also welcome.

Requirements:
· Master / PhD degree in a relevant academic subject area, such as computer science, graphical user interfaces, data mining, text mining, artificial intelligence, or advance statistics
· Experience in software design and computer programming (e.g. JavaScript, D3.js, HTML5, R, Python or other visualization techniques).
· Good analytical and statistical skills
· Proactive behavior and passionate about research and technology
· Creativity, self-management skills and cooperation skills
· Academic writing and presentation skills
· Good English skills (spoken and written)
· Willingness to learn German
· Preparedness to travel on a regular basis for international activities
· Knowledge about the Learning Analytics field is a plus

Generally, our employees should be skilled in becoming acquainted with further areas of work and respective demands at short notice. We expect successful candidates to demonstrate their personal commitment, ability to work in a team, communicate and co-operate.

We offer a modern workplace, good conditions for balancing work and family life, a pleasant atmosphere and perspectives for development, also for entrants.
Women are especially encouraged to apply. Applicants will principally be able to work part-time provided that job-related requirements are appropriately considered. Equally qualified people with disabilities will be particularly considered.

Please submit your application and standard documents – preferably in electronic format to bewerbung-izb@dipf.de, quoting the reference number of the position. You can find the original description of the position here:
PostDoc – Reference Number: IZB 2017-08 – Link: http://bit.ly/2uDNOg4
PhD 1 – Reference Number: IZB 2017-10 – Link: http://bit.ly/2u4u0zA
PhD 2 – Reference Number: IZB 2017-09 – Link: http://bit.ly/2u4g5JD
The closing date is 17.08.2017. Applications should be addressed to Professor Dr. Hendrik Drachsler, PO Box 900270, 60442 Frankfurt am Main. If you have any further questions, please get in contact with Prof. Dr. Drachsler: drachsler@dipf.de.

Author Hendrik Drachsler

Dr. Hendrik Drachsler is Associate Professor for Personalised Learning Technologies at the Welten Institute of the Open University of the Netherlands. His research interests include Learning Analytics, Personalisation technologies, Recommender Systems, Educational data, mobile devices, and their applications in the fields of Technology-Enhanced Learning and Health 2.0. He is chairing the EATEL SIG dataTEL and the national SIG Learning Analytics of the Dutch umbrella organisation SURF. He is elected member of the Society of Learning Analytics Research (SoLAR). In the past he has been principal investigator and scientific coordinator of various national and EU projects (e.g., FP7 laceproject.eu, patient-project.eu, WP2 lead LinkedUp-project.eu). He has regularly chairing international scientific events and is Associate Editor of IEEE's Transactions on Learning Technologies, and the Journal of Learning Analytics.

More posts by Hendrik Drachsler

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