Machine learning for advanced control of autonomous systems. We are continuously looking for outstanding students who are eager to do their Master thesis on a challenging project in the area of Learning Control.
Student Project Position
Submit your application to:
strimpe@tuebingen.mpg.de
Contact:
Sebastian Trimpe
Contact: Sabrina Jung
Contact: Sabrina Jung
Cyber Valley is a new center for AI research, bringing together partners from science and industry to create a world-leading hub for research in intelligent systems. The Max Planck Institute for Intelligent Systems, the University of Stuttgart, and the University of Tübingen invite applications for Independent Research Group Leaders in the Cyber Valley Initiative.
Submit your application to:
applications@cyber-valley.de
Contact:
Matthias Tröndle
Student Position
Contact: Raffi Enficiaud Sabrina Jung
Student Position
Contact: Sabrina Jung Naureen Mahmood
Graduate Position
Contact: Sabrina Jung
Graduate Position
Contact: Sabrina Jung Naureen Mahmood
Student Position
Contact: Sabrina Jung
Join us at the Max Planck Institute for Intelligent Systems, in Tübingen, Germany, a leading center of research excellence in the fields of Computer Vision, Machine Learning, and Robotics. Our research seeks to understand the principles of Artificial Intelligence by analyzing, modeling and building intelligent systems.
Graduate Position
Contact: Sabrina Jung Jojumon Kavalan
Open positions for PhD Students and Postdocs at the Autonomous Learning Group with Dr. Georg Martius at the Max Planck Institute for Intelligent Systems, Tübingen, Germany Details: http://georg.playfulmachines.com/ - section-182
Graduate Position
Submit your application to:
georg.martius@tuebingen.mpg.de
Contact:
Georg Martius
Sabrina Jung
2 open PhD positions in capturing and modelling virtual people from 4D scans, images and video. The PhD position is funded for a duration of 3-4 years. While the computer vision community has seen significant progress in detecting and tracking people in images using deep learning, most approaches are still 2D. The goal of the project is to build the most realistic generative model of 3D people in clothing from real measurements. One part of the project involves “capture”: that means tracking and estimating body shape, soft-tissue and cloth dynamics from data. The other part of the project involves “modelling”: using machine learning techniques the aim is to build models of humans in clothing that generalise to novel human shapes, movements and clothing. The research will have an impact in several fields such as medicine and artificial intelligence which requires to track and estimate the human movement and cloth from incomplete sensory data. The PhD student will work on state-of-the-art research at the intersection between computer vision, computer graphics and machine learning.
PHD Position
Submit your application to:
gerard.pons.moll@tue.mpg.de
Contact:
Gerard Pons-Moll
We are looking for a Big Data Engineer for our Central Scientific Facility "Scientific Computing" to develop a Big Data technology ecosystem
Graduate Position
Submit your application to:
personal@vw.mpi-stuttgart.mpg.de
Contact:
Sabrina Jung
Jojumon Kavalan
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.
Submit your application to:
tml-sekretariat@inf.uni-tuebingen.de
Contact:
Ulrike von Luxburg
Sabrina Jung
We are looking for students interested in developing novel algorithms for machine intelligence.
PHD Position
Submit your application to:
ph@tue.mpg.de
Contact:
Philipp Hennig
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen is looking for a highly motivated visiting PhD student interested in computer vision and machine learning. The visit is supported by a scholarship of MPI for a duration of 6 months. The applicant must hold a Master's degree and should currently be enrolled in a PhD program at a university or research institution. The project involves building statistical models of cloth garments and their dynamics from 4D scan data. The conducted research is expected to highly impact both science as well as industry in the short and long term.
Contact: Gerard Pons-Moll
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen is looking for a highly motivated visiting PhD student interested in computer vision and machine learning. The visit is supported by a scholarship of MPI for a duration of 6 months. The applicant must hold a Master's degree and should currently be enrolled in a PhD program at a university or research institution. At the Perceiving Systems Department we are interested in building digital models of humans and clothing. Being able to parse clothing from different data modalities (4D scans, video or Kinect) is central to building such models and to perceive humans in the wild. The role of the student will be to infer human pose, shape and 3D garment geometry from video and Kinect data. The conducted research is expected to highly impact both science as well as industry in the short and long term.
Graduate Position
Contact: Gerard Pons-Moll
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen is looking for a highly motivated visiting PhD student interested in computer vision and machine learning. The visit is supported by a scholarship of MPI for a duration of 6 months. The applicant must hold a Master's degree and should currently be enrolled in a PhD program at a university or research institution. The project involves combining ideas from physical simulation and data-driven models to learn models of soft-tiusse motions from thousands of 4D scans. Experience in physically based simulation is a plus. The conducted research is expected to highly impact both science as well as industry in the short and long term.
Graduate Position
Contact: Gerard Pons-Moll
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen is looking for a highly motivated visiting PhD student interested in computer vision and machine learning. The visit is supported by a scholarship of MPI for a duration of 6 months. The applicant must hold a Master's degree and should currently be enrolled in a PhD program at a university or research institution. The student will work on state-of-the-art research at the intersection of computer vision, computational photography and machine learning, closely supervised by a researcher from MPI Tübingen. The conducted research is expected to highly impact both science as well as industry in the short and long term.
Contact: Andreas Geiger
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen and the Robert Bosch GmbH in Leonberg are looking for a highly motivated PhD student interested in computer vision and deep learning. The duration of the fully funded PhD is 3 years and the student will work 50% of the time at the MPI for Intelligent Systems, Tübingen and 50% of the time at the Robert Bosch GmbH, Leonberg. Thus, this position provides an excellent link between academia and industry. The student will be supervised by a researcher from MPI Tübingen and a researcher at Robert Bosch GmbH and therefore benefit from both environments. The conducted research is expected to have a high impact on science as well as in industry.
PHD Position
Contact: Andreas Geiger
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen is looking for a highly motivated PhD student interested in computer vision and machine learning. The three year PhD scholarship is sponsored by Microsoft Research Cambridge (UK) and the PhD student will be based at the Max Planck Institute for Intelligent Systems in Tübingen with regular visits at Microsoft Research Cambridge. The PhD student will work on state-of-the-art research in computer vision and machine learning, being co-supervised by a researcher from MPI Tübingen and Microsoft Research Cambridge. The conducted research is expected to highly impact both science and industry in the short and long term.
PHD Position
Contact: Andreas Geiger
In a new research project, we seek to integrate recent advances in wireless networking with networked control to develop a superior solution for reliable and economic wireless control for cyber-physical systems (CPSs). We are looking for outstanding students who are interested in doing their Master thesis in this novel, interdisciplinary, and challenging research area. Depending on the student's background and interests, the project can involve fundamental theoretical developments, extensive simulation studies, as well as applied work around developing a novel CPS demonstrator.
Student Project Position
Submit your application to:
strimpe@tuebingen.mpg.de
Contact:
Sebastian Trimpe
Structured prediction refers to machine learning models that predict multiple interrelated and dependent quantities. Many applications in a wide range of domains can naturally be understood in this way. A wide variety of expressive and powerful models have been proposed, mostly tailored to specific applications. A shared common problem amongst many structured prediction models is that of intractable inference. This results in inefficient computation and in turn reduces the practical significance. We propose to study structured prediction models in the context of sequential decision making. Each decision is allowed to depend on a rich context that includes previous decisions as well as context-dependent observations. This approach puts emphasis on tractable inference and we believe that progress in this field will result to practical impact in multiple applications.
This PhD position is sponsored by Microsoft Research and is co-supervised by Peter Gehler, Max Planck Institute for Intelligent Systems and Sebastian Nowozin, Microsoft Research Cambridge.
PHD Position
Contact: Peter Vincent Gehler
Outstanding candidates in all areas of computer vision will be considered but special emphasis will be given to candidates with experience in modeling and estimating human and animal shape including 3D mesh models, statistical shape modeling, 3D vision, articulated pose estimation, and non-rigid models of clothing, hair and fur. While our focus is basic research, we also pursue commercial applications and applications in neuroscience.
PostDoc Position
Contact: Melanie Feldhofer
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.
PHD Position
Contact: Andreas Geiger
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.
PHD Position
Contact: Melanie Feldhofer
Internship in 3D Computer Vision at the MPI for Intelligent Systems in Tübingen
Contact: Andreas Geiger
The Perceiving Systems department at the Max Planck Institute for Intelligent Systems in Tübingen, Germany announces several PhD scholarships as well as funded summer internships for graduate students in 2016. Research at Perceiving Systems is curiosity driven and spans a wide range of topics in computer vision, graphics and machine learning.
PHD Position
Contact: Michael Black Andreas Geiger Peter Vincent Gehler Javier Romero
The MPI for Intelligent Systems is in the process of identifying candidates for a new Director. Our institute seeks 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.
Staff Position
Contact: Sabrina Jung
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