Research Assistant / PhD Position (m/f/d), EG 13 TV-H

This is a full-time position initially offered for three years (an extension of the initial contract is possible) within the DFG project “ReNO: Resilient Integration of Machine Learning for Enhanced Network Operation” in accordance with § 2 Abs. 2 WissZeitVG. The opportunity to pursue a PhD is provided.

Due to the important role that communication networks, and the Internet in particular, play in our society, failures are seen as significant threats for our daily lives. The main reason behind these failures? Networks are becoming more and more complex. While network operators are already struggling to control and to configure well-established protocols to patch failures or to prepare the Internet for new technologies. Yet, network operators get left behind with their traditional network operation tools and solutions. Machine learning based network management solutions propose a way to handle complexity in network management. Yet, ML can itself harm network resilience by making wrong decisions and being used as black-box solutions that cannot be fully understood. The goal of this project is to improve network resilience by identifying situations in which machine learning helps in making networks more resilient.

Tasks:

• Conducting independent and cutting-edge research in the field of computer networks, focusing on areas such as BGP-based traffic engineering and enhancing routing/infrastructure resilience and cybersecurity.
• Developing machine learning solutions and assessing their potential to enhance network resilience.
• Publishing your research findings in top-tier peer-reviewed international conferences.
• Collaborating with other researchers (national and international). The project is part of a priority program of the German National Science Foundation (www.resilient-worlds.org/). Thus, the active collaboration with researchers within and beyond Resilient Worlds is expected.

Requirements:

• A good to very good master's degree (or equivalent) in Computer Science or closely related disciplines. The degree must be obtained
• by the recruitment date at the latest.
• Good to very good knowledge in machine learning and computer networks.
• Very good programming/scripting skills (e.g., Python, Bash)
• A strong passion for scientific challenges and the drive for independent and goal-oriented research.
• Very good proficiency in English, with a good working knowledge of German being an advantage.
• Very good scientific communication and writing skills.

Advantageous are:

• Linux/Unix skills
• Knowledge in Traffic Engineering / BGP
• Knowledge in Performance Evaluation of computer systems and their statistical evaluation

Application Material:

• A cover letter (max. 1 page) detailing your motivation for applying to the position, explaining how your qualifications and skills align
• with the distributed systems group and the project, and highlighting your research interests.
• A detailed Curriculum Vitae.
• A copy of your degree certificate, including a complete transcript of courses taken, or a certified list of completed courses with grades
• and dates.
• A PDF copy of your master's thesis or an equivalent research project.
• If applicable, copies of publications or certificates related to other qualifications.

For further information please contact Prof. Dr. Oliver Hohlfeld, Tel.: +49 561 804-6275 , Deadline for submission: in 4 weeks

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,
• your workplace is centrally located in the city of Kassel with good public transport connections, which you can currently use for free.

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.