Skip to content

Details Job vacancies

1 x 1,0 Early Stage Researcher position (f/m/d)

Early Stage Researcher position

At the University of Bremen the Institute for Artificial Intelligence calls for applications in the area of Artificial Intelligence and Robotics – under the condition of job release – for the following position:

Early Stage Researcher in Machine Learning for Robotic Systems


Salary Scale TV-L 13 (100 %), start date: as soon as possible.
The position is a fixed term position until October 31, 2022.

Reference Number: A232/19

The employment is fixed-term and governed by the Act of Academic Fixed-Term Contract, §2 I (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.

The position is part of the research project „PIPE – Probabilistic Models of Instructions, Perception and Experience – Representation, Learning and Reasoning“.

The project investigates methods in the field of machine learning and data mining for cognitive robotic systems, which aim at combining the humans‘ capability of understanding natural language, perceiving objects in the environment and learning from experience. In particular, we want to equip robots with the ability to autonomously acquire knowledge in order to proficiently act in human environments and competently and successfully achieve their goals.

Tasks:

  • Develop and implement machine learning models and algorithms for the learning of and reasoning about complex relations among data sources relevant for intelligent autonomous robots
  • Create documentation and presentations of research results at international scientific conferences
  • Work independently and enthusiastically in close collaboration with project partners
  • Contribute to research fund proposals and public relation activities

Requirements:

  • Excellent Master‘s degree in computer science with major in artificial intelligence and/or machine learning (or equivalent).
  • Excellent skills in theory and practice of machine learning/data mining methods, ideally experience with probabilistic graphical models.
  • Excellent programming skills in the Python programming language, C/C++ is beneficial
  • Experience in software development under Linux
  • Excellent oral and written level in English, especially in technical English. Skills in German is beneficial.
  • Very good organizational skills and team spirit

We are searching for an enthusiastic and dynamic colleague who is interested in joining a multidisciplinary research team. Applicants should have distinct profiles that show their potential to substantially contribute to research programme of the project. This can be demonstrated through experience in the realization of machine learning and data mining systems, expressive github profiles, being a key member of programming teams participating in competitions, etc.

The University of Bremen has received a number of awards for its diversity policies and offers a family-friendly working environment as well as an international atmosphere.
The University is committed to a policy of providing equal employment opportunities for both men and women alike, and therefore strongly encourages women to apply for the positions offered. Applicants with disabilities will be considered preferentially in case of equal qualifications and aptitudes. The University of Bremen explicitly invites individuals with migration backgrounds to apply.

If you have any questions regarding the position, please contact Prof. Michael Beetz, PhD (ai-officeprotect me ?!cs.uni-bremenprotect me ?!.de).
Applications including a cover letter, CV, publication list, copies of degree certificates, should be submitted by 8thSeptember, 2019 to:

Prof. Michael Beetz, PhD
Artificial Intelligence / Universität Bremen
Am Fallturm 1
28359 Bremen

or by Email (including up to two PDF files; reference number) to: ai-officeuni-bremen.de

The costs of application and presentation cannot be reimbursed.

 

Created on 02.08.19 by Rebekka Rosner