Research Assistant/Associate (f/m/d)
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Lehrstuhl für Informatik 6 (Maschinelles Lernen)
The Representation, Learning, and Planning Lab (RLeap) is a new research lab within the Chair of Machine Learning and Reasoning at RWTH Aachen. The lab and the chair are headed by Prof. Dr. Hector Geffner, an Alexander von Humboldt Professor in the Computer Science Department. The aim of the lab is the development of methods and representations for learning to act and plan in ways in which the learned components can be reused in a flexible and goal-oriented manner. The research is funded by the Humboldt Foundation, an Advanced ERC Grant, and RWTH Aachen, and builds on ideas and methods from different areas in AI and Machine Learning: deep learning and deep reinforcement learning, planning and knowledge representation and logic and and combinatorial optimization. Our approach is a form of top-down representation learning based on a clear separation between what is to be learned and how. More generally, we seek a tight integration of data-based learners and model-based reasoners (solvers) that can inform, enhance, and complement each other in order to make AI systems that are more reliable, more transparent, and more adapted to human interaction.
Details at https://www-i6.informatik.rwth-aachen.de/~hector.geffner/rleap.html.
We are looking for highly motivated and talented PhD students with a strong technical background that are eager to join us and make a difference in these problems.
You have a university degree (master's or equivalent) in computer science or related discipline.
You have solid technical background in CS, AI, and ML and a strong interest in research.
You have have taken a look at some of our papers.
You are a very good programmer and like to do experimental work in CS.
You know logic and theory, and can assimilate theoretical work.
You have a crisp sense of understanding and need to understand things deeply.
You can supervise Bachelor and Master students.
You have excellent language skills (English).
Your Duties and Responsibilities
You will do cutting-edge research in one of the top groups in planning and learning.
You will present your work at top conferences and leading journals.
You will supervise Bachelor and Master students working on related topics.
You will have some involvement in teaching.
You will help in other academic or administrative tasks if needed.
Interested candidates should send a CV, transcripts, two recommendation letters, and a motivation letter to Stephanie Jansen, preferably to: firstname.lastname@example.org.
What We Offer
The successful candidate will be employed under a regular employment contract.
The position is to be filled at the earliest possible date and offered for a fixed term of 2 years initially.
Continued employment for at least 3 years in total as part of the doctoral degree is planned.
The fixed-term employment is possible as it constitutes one of the fixed-term options of the Wissenschaftszeitvertragsgesetz (German Act on Fixed-term Scientific Contracts).
This is a full-time position.
The successful candidate has the opportunity to pursue a doctoral degree in this position.
The salary is based on the German public service salary scale (TV-L).
The position corresponds to a pay grade of EG 13 TV-L.
RWTH is a certified family-friendly University. We support our employees in maintaining a good work-life balance with a wide range of health, advising, and prevention services, for example university sports. Employees who are covered by collective bargaining agreements and civil servants have access to an extensive range of further training courses and the opportunity to purchase a job ticket.
RWTH is an equal opportunities employer. We therefore welcome and encourage applications from all suitably qualified candidates, particularly from groups that are underrepresented at the University. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of national or ethnic origin, sex, sexual orientation, gender identity, religion, disability or age. RWTH is strongly committed to encouraging women in their careers. Female applicants are given preference if they are equally suitable, competent, and professionally qualified, unless a fellow candidate is favored for a specific reason.
As RWTH is committed to equality of opportunity, we ask you not to include a photo in your application.
You can find information on the personal data we collect from applicants in accordance with Articles 13 and 14 of the European Union's General Data Protection Regulation (GDPR) at http://www.rwth-aachen.de/dsgvo-information-bewerbung.
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Lehrstuhl für Informatik 6 (Maschinelles Lernen)
Applicants are invited to submit their applications via email. For data protection reasons, however, we recommend sending applications via mail.