Academic research assistant in Saarbrücken bei Universität des Saarlandes

Saarland University is a campus university with an international reputation for research excellence, particularly in

computer science and in the life sciences and nanosciences. The university is also distinguished by its close ties to

France and its strong European focus. Around 17,000 students, studying over one hundred different academic

disciplines, are currently enrolled at Saarland University. Saarland University is officially recognized as one of

Germany’s family-friendly higher-education institutions and with a combined workforce of more than 4000 it is one

of the largest employers in the region.

The Research Training Group "Neuroexplicit Models of Language, Vision, and Action" is inviting applications for the

following position commencing 01 September 2024

Academic research assistant (m/f/x)

Reference number W2411, salary in accordance with the German TV-L salary scale1, pay grade: E13 TV- L, duration

of employment: 4 years, volume of employment: 100 % of standard working time.

Workplace/Department:

The RTG "Neuroexplicit Models of Language, Vision, and Action" develops novel models to accurately solve tasks in

natural language processing, computer vision, and action-decision making. Neuroexplicit models combine neural and

human-interpretable ("explicit") components; these include e.g. symbolic and physics-based models. We aim to

improve the state of the art through the use of neuroexplicit models and investigate general machine learning design

principles for effective neuroexplicit models.

The RTG will fund up to 24 PhD students at a time and brings together multiple world-class research institutions on

the Saarland University campus. We aim to recruit internationally and create a tight-knit, interdisciplinary research

group through a joint qualification program. For more information, see https://www.neuroexplicit.org/

Job requirements and responsibilities:

• Your job will be to carry out research with international impact within or across the fields of natural language

processing ("Language"), computer vision ("Vision"), planning or reinforcement learning ("Action"), and machine

learning ("Foundations"). You will choose your research topic freely in coordination with your PhD advisors.

• The position is designed to enable you to obtain a PhD in Computer Science within four years.

Your academic qualifications:

• Completed scientific university studies in computer science, artificial intelligence, computational linguistics, visual

computing, or a related discipline (a completed Master's degree).

1 TV-L = collective agreement on remuneration of public sector employees in the German Länder

The successful candidate will also be expected to:

• Demonstrated expertise in one of the research fields of the RTG, e.g. through an excellent Master's thesis or

relevant publications.

• Language skills (according to GER): English C1

What we can offer you:

• A flexible work schedule allowing you to balance work and family, among other things the possibility of

teleworking

• Secure and future-oriented employment with attractive conditions

• A broad range of further education and professional development programmes (for example language courses)

• An occupational health management model with numerous attractive options, such as our university sports

programme

• Supplementary pension scheme (RZVK)

• Discounted tickets on local public transport services (‘Job-Ticket Plus‘ of the saarVV)

We look forward to receiving your meaningful online application (in a single PDF file) with the following information

• A CV that describes your education and work history, any particular achievements, and your publications (if any).

• Transcripts of your academic degrees and, if possible, a copy of your MSc diploma.

• A research proposal (1-2 pages) that outlines your research interests with respect to the topic of the RTG.

• The research area(s) that interest you most (Language, Vision, Action, Foundations) and a list of up to three PhD

advisors you would most like to work with.

• Names and e-mail addresses of two academic references.

by 07 January 2024 to apply@neuroexplicit.org . Please include the reference number W2411 in the subject line

of the e-mail.

If you have any questions, please contact us for assistanc