Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems. The Institute studies these principles in biological, computational, hybrid, and material systems ranging from nano to macro scales.We take a highly interdisciplinary approach that combines mathematics, computation, material science, and biology.
The MPI for Intelligent Systems has campuses in Stuttgart and Tübingen. Our Stuttgart campus has world-leading expertise in small-scale intelligent systems that leverage novel material science and biology. The Tübingen campus focuses on how intelligent systems process information to perceive, act and learn.
The Tübingen Campus for Intelligent Systems consists of the following departments:
The Autonomous Motion Department has its focus on research in intelligent systems that can move, perceive, and learn from experiences. We are interested in understanding, how autonomous movement systems can bootstrap themselves into competent behavior by starting from a relatively simple set of algorithms and pre-structuring, and then learning from interacting with the environment. Using instructions from a teacher to get started can add useful prior information. Performing trial and error learning to improve movement skills and perceptual skills is another domain of our research. We are interested in investigating such perception-action-learning loops in biological systems and robotic systems, which can range in scale from nano systems (cells, nano-robots) to macro systems (humans, and humanoid robots).
The problems studied in the department can be subsumed under the heading of empirical inference. This term refers to inference performed on the basis of empirical data. The type of inference can vary, including for instance inductive learning (estimation of models such as functional dependencies that generalize to novel data sampled from the same underlying distribution), or the inference of causal structures from statistical data (leading to models that provide insight into the underlying mechanisms, and make predictions about the effect of interventions). Likewise, the type of empirical data can vary, ranging from sparse experimental measurements (e. g., microarray data) to visual patterns. Our department is conducting theoretical, algorithmic, and experimental studies to try and understand the problem of empirical inference.
How do we see? We seek mathematical and computational models that formalize the principles of perception. Can we make computers that see? We combine insights from neuroscience with statistical models, machine learning, and computer graphics to derive new computer vision algorithms that, one day, may enable computers to understand the visual world of surfaces, materials, light and movement
Our research area is machine learning and computational biology, in particular machine learning in systems biology. Machine learning is concerned with the development of efficient algorithms and mathematical models for finding patterns and statistical dependencies in large volumes of data.
We develop machine learning methods for exploring the molecular networks underlying complex phenotypes, currently with a focus on the genetic foundations of these traits. First, this involves methods for accurately genotyping individuals, for instance, by SNP imputation or by structural variant detection. Second, this includes methods for accurate phenotyping, for instance via biological image analysis or by confounder correction. Third, our research addresses the question of how to measure association between genotype and phenotype, for instance, by two-locus association mapping or by pathway mapping.
We are part of the 1001 Genomes Project in Arabidopsis thaliana, collaborating with Prof. Dr. Detlef Weigel's department at the MPI for Developmental Biology. We also explore the use of machine learning methods for open problems in data-driven Medicine, in collaborations with the MPI for Intelligent Systems (Prof. Dr. B. Schölkopf), the MPI for Psychiatry (Prof. Dr. B.Müller-Myhsok), and the Broad Institute (Prof. Dr. M. Daly). Our ultimate goal is to develop machine learning methods that enable personalized medical treatment.
In addition to the departments we are building three shared central scientific facilities:
Scientific Computing Facility builds and maintains the computing and storage infrastructure for the research in the institute. It includes X86 cluster, GPU cluster, and storage servers. Apart from supporting the day-to-day computing needs of the researchers, we love to collaborate with them to develop scalable applications, and parallelize and/or optimize algorithms and applications. We also conduct independent research on scalable computing aspects of Intelligent Systems.
The Service group is a small yet advanced "competence team" in which every person contributes his or her skills and knowledge in a constructive and creative way to provide the necessary administrative matters around the science:
Making Tübingen your home and not just your work place as quickly as possible is the aim of the Welcome Service. The Max Planck Institute for Intelligent Systems wants to welcome you by assisting you in settling in Tübingen, Germany. You are becoming not just part of an institute but of a community.
Here we try to answer general question on all topics that concern everyone who comes to Tübingen: directions, bus lines, dealing with authorities (visa, residence permit, etc.), house hunting, and becoming a PhD student.
Please notice the different deadlines!! All of the procedures mentioned above have to be completed before your visa expires. Some of them have to be completed in order for you to get paid by the MPI IS.
Higher education in Germany is not governed by federal but by state law. The state of Baden-Württemberg only provides a rather general legal frame work and leaves more detailed regulations up to the individual universities:
Nevertheless, the most important things you need to become a PhD student in Germany are the same all over Germany:
Only universities that are granted the right to have PhD students by the Standing Conference of the Ministers of Education and Cultural Affairs of the Federal States of Germany ("Kultusministerkonferenz") are allowed to award doctoral degrees.
Besides the basic requirements stated above, you need to find a second supervisor. This can be a qualified member of a non-university research institution like the Max Planck Society. Please make sure your university supervisor agrees with the outside supervisor.
Unlike most other universities, the University of Tübingen does not require you to enroll in order to be awarded a doctoral degree. Enrollment is essential if you want to enjoy student benefits, e.g. lower public transportation fares, or living in the dormitories.
For more detailed information please visit the university’s website:
Check out the career part of our website for vacancies and our international Max Planck Research School for Advanced Material (IMPRS-AM):
Take initiative and check out the homepages of our three departments in Tübingen:
Also our research group:
Tübingen suffers from a severe shortage of housing, especially affordable for students/PhDs.
Please give your housing situation some thought well before you arrive here.
Shared apartments and rooms and short term rentals; website available in English:
University accomodation for guests and employees, also available to MPI members if free; website available in English:
University’s dormitories, also available to MPI members if free; website available in English:
Even if you do not speak German, you might want to give German websites a try. There is a list of abbreviations commonly used in German real estate ads translated into English available - Please contact Petra Hühnert for this list!
Short term and limited term rentals; only available in German:
Local newspaper; only available in German; Placing an ad in the local newspaper also works well and is affordable (from about EUR 25):
Feel free to mention Max Planck – it might do the trick!
Real estate agents in Germany do not look for an apartment for you!
Their service consists of making their offers available to you and accompanying you when you visit an apartment. Be careful, you might be charged for these kinds of "services" !
Real estate broker that only charges you when you rent an apartment, available in English:
There is a list of short term accommodations available with me, if you feel that you need more time in Tübingen to look for an apartment.
The list of options given here is by no means complete. If you would like to add to the list, please let me know.
The Max-Planck-Society is one of the world's premier places to conduct visionary, high-risk, long term, and fundamental research. The Max-Planck-Institute for Intelligent System is always looking for new talents, from Ph.D. students to research scientists to junior professor levels.
What we care about is a strong commitment to top-notch academic research. We are interested in people who like to gain international experience, are strongly self-motivated, can integrate into a team, and who can drive creative and new ideas. Our MPI can offer unparalleled academic freedom, opportunity to work with the best equipment in the world, and to gain ample experience in international conferences and collaborations.
There are currently no open positions.
We are changing how 3D shape and motion are modelled and captured by developing new 4D capture systems and software. The role of the Motion Capture and 4D scanning Technical Supervisor is to manage all aspects of our evolving hardware and software systems. You will work directly with researchers on the development and use of these systems for capturing the 3D shape of the human body in motion.
The Perceiving Systems Department, headed by Michael J. Black (formerly of Brown University), pursues basic research in computer vision including
We are seeking students interested in building princpled statistical models for solving problems in Computer Vision and Machine Learning. You will work an international team interested in building the best possible shape models. For details, see the PDF.
Visual Scene Understanding is one of the fundamental challenges in computer vision. While recent advances in object detection, semantic image segmentation and classification have spurred novel interest in the subject, most existing approaches work on single images only. At MPI for Intelligent Systems in Tübingen we are interested in lifting semantic image segmentation into 3D and reasoning about objects spatially and temporally using multi-view video sequences taken from a movable platform driving through a city.
There are currently no open positions.
There are currently no open positions.