The newly established research group on learning theory, headed by Ulrike von Luxburg at the Max Planck Institute for Intelligent Systems, Tübingen, Germany, is looking for a Postdoc and for a PhD student in the area of machine learning theory, particularly in the domain of comparison-based and ordinal data analysis, starting early 2017.
Ordinal data analysis is a new branch of machine learning and statistics, where relationships between data points are not given in the form of similarity or distance functions. Instead, we just get information of the form "the distance between objects i and j is smaller than the distance between objects u and v". The fundamental question is how we can perform statistics and machine learning based on this restricted information. Research questions in this area are abundant and largely unsolved. We are mainly interested in theoretical and algorithmic aspects. Because there does not yet exist a "default framework" in which the questions are usually solved, modeling and formalizing problems is an important aspect of the work, before we can then prove theorems and run computer simulations. The methods and tools we use come from the areas of learning theory, statistics, and geometry.
The postdoc position is full time (100%), on the German E13 pay scale of the Collective Wage Agreement for the Public Service (TVöD Bund), initially for two or three years (and can be extended longer). A successful postdoc candidate should have a PhD degree with focus in machine learning theory, theoretical computer science, statistics, or related areas. He/she should have established a strong publication record. The PhD student will receive a PhD funding contract (initially for three years) equivalent in remuneration to pay group E13 65% of the Collective Wage Agreement for the Public Service. The successful PhD candidate should have a Master’s degree either in mathematics (preferably with focus on probablity theory, statistics or geometry, and with good programming skills) or computer science (with a strong background in mathematics). Knowledge in machine learning is helpful, but not mandatory. The starting date for the two positions is flexible, ideally in the first months of 2017.
The two people will be embedded in the vibrant Max Planck Institute for Intelligent Systems in Tübingen, a world-class centre for foundational research in machine learning, computer vision, robotics and material science. There are close contacts to Ulrike von Luxburg's research group at the University of Tuebingen (which is in walking distance from the Max Planck Institute). Tübingen is a scenic medieval university town, cradled in what is simultaneously one of Germany’s most beautiful landscapes.
How to apply
Please send your electronic applications quoting reference number 82.16 by email to Celine Wieders (email@example.com), according to our application guidelines. Evaluation of candidates starts in October 2016 and will continue until the position is filled.
The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. The Max Planck Society seeks to increase the number of women in those areas where they are underrepresented and therefore explicitly encourages women to apply.