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The University of Kassel is a modern and growing University with round about 22.000 students. The university’s wide range of expertise covers subjects in the natural, applied, cultural and social sciences.

In the Department of Electrical Engineering/Computer Science, in the junior AI group GAIN ("Graphs in Artifical Intelligence and Neural Networks") (Dr. Thomas) at the Department of Intelligent Embedded Systems (IES) (Prof. Dr. Sick), the following position is to be filled as soon as possible:

Research Assistant (m/w/d), EG 13 TV-H, fixed term-position, part-time/full-time (currently 20-40 hours per week)

Application deadline:

24.06.2024

Date of hire:

as soon as possible

vacancy number: 37400

50% to 100% of a full-time employee. The position is initially limited until 31.12.2024 as part of the "GAIN" project in accordance with § 2 para. 2 WissZeitVG.


The junior research group GAIN works on machine learning on graphs, in particular graph neural networks (GNNs), their dynamics, expressivity and applications in energy systems.

With us, you can work in one of the youngest and most dynamic research fields within Deep Learning - Graph neural networks. GAIN is a creative and dedicated team of scientists from different disciplines. Our way of working is cooperative, with a pleasant and productive atmosphere, and openness and appreciation in our dealings with each other are essential to us. You can pursue your enthusiasm in programming with us on a large compute cluster with graphic cards.


Tasks:

  • Scientific colaboration in the GAIN project, in particular:
    • development of GNN algorithms for dynamic graphs,
    • development of methods of explainability for dynamic GNN algorithms,
    • performing simulations to evaluate the developed algorithms and methods,
    • evaluation of the algorithms using appropriate statistical methods,
    • publication of research results
  • Participation in organizational tasks (e.g., project meetings, project reports)


Requirements:

  • Academic university degree in Computer Science or closely related field of study completed with at least good results. The required degree must be available by the recruitment date at the latest.
  • Very good skills in programming, especially in Python
  • Good knowledge of Machine Learning, especially Neural Networks
  • Good knowledge of English


Advantages are:

  • Knowledge in discrete mathematics (basics of graph theory)
  • Knowledge in programming graph neural networks
  • Knowledge of the german language
  • Knowledge in data analysis and data processing


To apply, please send your CV, a short and concise motivation letter and an overview of the courses of your highest university degree with grades via the online-form.

For further information please contact Dr. Josephine Thomas, jthomas(at)uni-kassel.de


Our Offer:

As an employee of the University of Kassel

  • you will be offered an interesting and diverse range of tasks within the framework of a modern and ambitious university,
  • you will be part of an interdisciplinary team with a good and collegial working atmosphere,
  • you will have the opportunity to participate in professional and interdisciplinary further education measures,
  • is your workplace with good connections to public transport, which you can currently use free of charge.

In addition, you will benefit from the advantages of employment in the public service such as:

  • an additional company pension (VBL),
  • an optional child supplement in accordance with TV-Hessen, a family-friendly university (including childcare for emergencies),
  • an annual bonus
  • an entitlement to capital-accumulation benefits,
  • a promotion of voluntary commitment,
  • low-cost participation in university sports and a full range of fitness activities as part of Unifit, as well as workplace health management

You can find more jobs at stellen.uni-kassel.de

Please send your application with the usual informative documents, stating the reference number in the subject line, via the online form. We have compiled further information for you in our FAQ.

In exceptional cases, we will also accept your application documents in paper form addressed to: The President of the University of Kassel, 34109 Kassel, Germany, or via mail to bewerbungen[at]uni-kassel.de, stating the reference number.

In the case of postal applications, please submit only copies of your documents (no folders), as these cannot be returned. All documents will be destroyed after completion of the selection process in compliance with data protection regulations.

The protection of your personal information is very important to us, so we will handle your personal information with care. By your application, you allow us the storage and use in the sense of the Hessian Data Protection and Freedom of Information Act. You can object to this at any time. Your personal data will be deleted.

Information according to Art. 13 DSGVO for the application process at the University of Kassel can be found at:
www.uni-kassel.de/go/ausschreibung-datenschutz

Information and FAQ about applying for a job offer:

https://www.uni-kassel.de/uni/universitaet/stellenangebote/hinweise-und-faq-zur-bewerbung-auf-ein-stellenangebot

The University of Kassel is very interested in the professional satisfaction of its employees. It is distinguished as a family-friendly university and, in the interests of equal opportunities, strives to offer everyone the same opportunities for development and to counteract existing disadvantages. It promotes the Family Welcome Service and also the Dual Career Service for positions that are scientifically and academically filled. One of the strategic goals of the University of Kassel is to significantly increase the proportion of women in research and teaching. Applications from women are therefore particularly welcome. Seriously handicapped and equivalent applicants are given preference if they have the same suitability, qualifications and professional performance. Full-time positions are generally divisible (except when filling civil servant positions). Applications indicating the Position Number, which may be in digital form, should be sent to the President of the University of Kassel, 34109 Kassel, Germany quoting the applicable reference number.


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