Institute
Open Positions

Open Positions

  • Unsolicited Application (m/f/d) within the field of Automated Machine Learning (AutoML Group)

    On a regular basis, we have open positions. Since opening an official call takes some time, we encourage you to send us unsolicited applications if you should be interested in working with us. (Last updated July 2022)

     

    Your Profile

    • completed academic degree (Master) in artificial intelligence, machine learning, computer science, statistics, or related disciplines
    • Solid understanding of and hands-on experience with machine learning and deep learning
    • Advanced programming skills in Python, preferably familiarity with PyTorch
    • Solid skills in scientific writing (e.g. shown by an excellent master thesis for PhD candidates, or published papers for PostDocs) are expected
    • Excellent communication skills in English, both oral and written, including the ability to write scientific texts (German beneficial)
    • Motivation to work independently and in an international team

     

    Further (optional) beneficial skills can include:

    • AutoML
    • Hyperparameter optimization
    • Neural architecture search
    • Reinforcement learning
    • Interpretable machine learning
    • Meta-Learning and transfer learning
    • Bayesian optimization
    • Algorithm configuration 
    • Algorithm selection
    • Evolutionary strategies

    The concrete future research topic has to be in the field of AutoML.

     

    Typically, such a position comes with salary at the level of 100% of salary scale 13 according to the Collective Agreement for the Public Service of the Länder (TV-L),  with a monthly gross salary between 4000 EUR and 4600 EUR, depending on experience and previous position.

     

    Please submit your application with supporting documents as described in How to Apply? additionally including:

    • Earliest, preferred and latest possible start date
    • At least 2 references (only for PostDocs!)
      • For each reference, please include name, title, and email address.
      • References should expect to be contacted for a reference letter.

     

    For further information, please contact Marius Lindauer.

  • Student assistant for the AutoML group

    Our research team at Leibniz Universität Hannover focuses on Automated Machine Learning (AutoML), Machine Learning and Reinforcement Learning. We are looking for a motivated student assistant to provide programming support to our team. We offer you the opportunity to help shape open source projects and thus promote the further dissemination of research results and advance the field of explainable and interactive ML. This involves maintaining and expanding existing libraries as well as supporting the implementation of new approaches and the associated experimental evaluation. We will match the focus and type of work with your skills and preferences over time.

    Your Profile

    • Enrolment at a German university in the fields of artificial intelligence, machine learning, computer science, statistics or related disciplines.
    • Bachelor's degree at the most.
    • Basic understanding of machine learning, practical experience an advantage.
    • Programming skills in Python, preferably experience with libraries such as scikit-learn, PyTorch or SMAC.
    • Good communication skills in English, both oral and written.
    • Motivation to work independently and to work in an international team.

    We offer

    • Varied, creative and innovative work in a young, diverse team.
    • Collaboration with scientific staff.
    • First insights into scientific work - especially interesting if you are interested in a scientific career.
    • Gaining practical experience in the implementation and experimental evaluation of machine learning approaches.
    • Remuneration of 12€/h without B.Sc., 12,77€/h with B.Sc.

    The university has set itself the goal of particularly promoting the professional equality of women and men. To this end, it strives to reduce underrepresentation in areas where one gender is underrepresented. Women are underrepresented in the pay group of the advertised position. Qualified women are therefore invited to apply. Applications from qualified men are also welcome. Severely disabled persons will be given preference in case of equal qualification.

    Please send your application with the usual documents (CV, certificates, a short explanation of max. half a page what drives you to deal with (explainable and interactive) AutoML, and what goals you are pursuing with your application to AutoML Hannover) digitally in a PDF file by 31.08..2023 to office@ai.uni-hannover.de  , or by post to:
    Gottfried Wilhelm Leibniz University of Hannover
    Institute for Artificial Intelligence
    Appelstrasse 9a
    30167 Hanover

    www.uni-hannover.de/jobs   

    Information according to Article 13 DSGVO on the collection of personal data can be found at https://www.uni-hannover.de/de/datenschutzhinweis-bewerbungen/ .

Leibniz University Hannover considers itself a family-friendly university and therefore promotes a balance between work and family responsibilities. Part-time employment can be arranged upon request.

The university aims to promote equality between women and men. For this purpose, the university strives to reduce under-representation in areas where a certain gender is under-represented. Women are under-represented in the salary scale of the advertised position. Therefore, qualified women are encouraged to apply. Moreover, we welcome applications from qualified men. Preference will be given to equally-qualified applicants with disabilities.

How to Apply?

Please submit your application with supporting documents including

  • CV
  • Full set of transcripts
  • Brief statement of at most 1 page of what drives you to do research in the field of the open position (AutoML / NLP), and what your goals are in applying at AutoML / NLP Hannover

either digitally as a single PDF file to:

Email: office@ai.uni-hannover.de

or alternatively by mail to:

Gottfried Wilhelm Leibniz Universität Hannover
Institute of Artificial Intelligence
Appelstr. 9a, 30167 Hannover
Germany

Information on the collection of personal data according to article 13 GDPR can be found at https://www.uni-hannover.de/en/datenschutzhinweis-bewerbungen/.   

Q&A

  • Why AutoML Hannover?

    The group was founded in 2019 and is growing since then. We are a diverse group with strong feelings for the mission of AutoML: democratization of machine learning by supporting developers and users in efficiently creating new AI applications. We do a mix between basic and applied research with funded projects from industry, DFG, BMBF, BMWI, BMU and ERC. In particular, the ERC starting grant from Prof. Lindauer enables the group to open up new exciting research directions with excellent long-term funding. With several of his prior groups, Prof. Lindauer won many international, prestigious competitions, such as ASP and SAT competitions, AutoML competitions and black-box optimization for hyperparameter optimization. Besides publications at top-tier venues, open-source is at the heart of the research group, leading to increased visibility, improved reproducibility and fair research. 

  • Why Hannover?

    Hannover is at the center of Germany. Although Hannover is one of the greenest cities in Germany, it has an (undeserved) underdog image. As the capital of Lower Saxony, you can find in Hannover everything you are looking for, incl. concerts, museums, a big zoo, and all kinds of events and shopping opportunitiesIf you think this is not enough, you can take the train to go to Hamburg or Berlin within 1h and 30min.

  • Why the Leibniz University Hannover (LUH)?

    The LUH is neither one of these very young universities, nor one of these very old universities. It goes back to 1831 and these days it combines the best of both worlds by having 87 degree courses, roughly 30 000 students, being funded with more than 500 Mio Euro each year, and having more than 300 professors from all kinds of disciplines (source). Our faculty of electrical engineering and computer science combines the expertise in the most important areas for digitization. Close-by companies also allow to transfer research insights into relevant practical solutions and make it easy to find jobs after graduation.

  • Why PhD in Germany?

    First of all and in contrast to many non-EU countries, paid holidays (~30 days per year), paid sick leave, paid parental leave and health insurance are included. Furthermore,  in contrast to many other countries, you will receive a fairly good salary (see 100% E13 for Phd students and E14 for PostDocs), which is even competitive with the salary for a young researcher or research engineer at big tech companies in Germany. Furthermore, you will have fairly little obligations: besides doing your research, you can roughly expect to support the group and the institute one day per week (e.g., teaching) and depending on the funding of your contract, one day for working on a specific project (which will synergize with your PhD topic). So, you can work on your own (AutoML / NLP related) research at least 60% of your time — much more than in most other countries. If you are a PostDoc, you can even apply for your own grant money (e.g., via DFG) and start your own research group.

  • What are the steps of the application process for AutoML Group?

    We first check your documents (with a focus on the motivation letter). If your documents show promise, we will ask you to solve an AutoML-related coding task to show us that you can implement basic AutoML and ML/DL ideas. If that is also satisfying, we will have a roughly 2h interview (either on-site or virtual) checking your understanding of different topics and your expectations for this job. The last step is a short research presentation (e.g., about your master thesis topic) and a meeting with the entire group. You can expect that this process requires between 1 and 2 months before we can make the final decision whether to give you an offer or not. (Please note that for PostDoc applications, there are shortcuts for this process depending on prior experience.)