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jobs [2018/07/09 10:46] c7031007 [How to Apply] |
jobs [2022/03/13 10:06] Justus Piater |
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======Working With Us====== | ======Working With Us====== | ||
- | We are always looking for strong, motivated students to work on our [[theses|Bachelor or Master projects]]. | + | * We are hiring a tenure-track Assistant Professor in [[embodiedAI|Embodied AI and Machine Learning]]. |
+ | * We are always looking for strong, motivated students to work on our [[theses|Bachelor or Master projects]]. | ||
- | ===== Ph.D. Student Position in Robot Learning or Computer Vision at U. Innsbruck ===== | + | <html><!-- |
+ | ===== 2 Ph.D. Student Positions in Open-Ended Robot Learning at U. Innsbruck, Austria ===== | ||
- | The research group in [[@/|Intelligent and Interactive Systems]], led by Profs. Justus Piater and Antonio Rodríguez-Sánchez, has an opening for a Ph.D. student, on a university assistant position that includes minor teaching requirements. The research will be loosely aligned with ongoing [[:research:projects|research projects]] in the lab: | + | The [[@/|Intelligent and Interactive Systems]] group (Prof. Justus Piater and Dr. Matteo Saveriano) is looking for two talented Ph.D. candidates. |
- | * deep learning in computer vision or robotics | + | ====Scientific Context==== |
- | * computational models of biological vision | + | |
- | * biologically-inspired computer vision | + | We would like to be able to equip our robots with almost arbitrary skills in unconstrained environments. However, programming robot skills by hand is time consuming, and supervised and exploratory learning do not easily scale to complex and diverse tasks. Open-ended learning requires a combination of exploratory learning, explicit teaching, and the ability to reuse knowledge. |
- | * robot vision and closed-loop sensorimotor interaction | + | |
- | * open-ended and intrinsically-motivated robot learning | + | ====Position 1: Learning Large-Scale Robotic Knowledge Bases By Observing Humans==== |
- | * concept discovery by learning robots | + | |
- | * goal-oriented exploratory learning | + | The goal of this project is to enable robotic devices to acquire knowledge about the task execution from human observation and to build a large scale database of robotic tasks. Modern computing technologies, like noSQL, graph databases and cloud computing, are leveraged to populate and query the knowledge base and plan tasks on-line. A large knowledge base will allow the robot to execute a multitude of tasks and, more importantly, can potentially allow the robot to reuse its knowledge in different scenarios in order to learn novel behaviors by self-practice. The Ph.D. candidate will also try to overcome the current imitation learning paradigm where the human is the only source of knowledge by adopting a bidirectional paradigm where the robot uses already acquired knowledge to assist the human during the teaching. |
- | * prediction of action effects | + | |
- | * robot skill optimization | + | This is a university assistant position that includes minor teaching requirements. |
- | * human-robot interaction and collaboration | + | |
+ | ====Position 2: Teaching Robots the Essence of Tasks==== | ||
+ | |||
+ | Most current work in robot learning focuses on learning trajectories or on mapping perception to action. However, tasks are characterized by the achievement of specific post-conditions; it is these the robot should understand, along with means to achieve and verify them. The objective of this research is to leverage explicit human teaching and other means to focus the attention of the robot to the crucial aspects of its perception/action space that define the task, allowing it to acquire complex skills in open-ended scenarios. | ||
+ | |||
+ | This position is part of the new EGTC Euregio IPN //OLIVER - Open-Ended Learning for Interactive Robots//, with Prof. Angelika Peer (U. Bolzano) and Prof. Nicu Sebe (U. Trento). | ||
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* earned, or be about to earn, an M.Sc. degree or equivalent in computer science or other relevant area, | * earned, or be about to earn, an M.Sc. degree or equivalent in computer science or other relevant area, | ||
* an excellent academic record, | * an excellent academic record, | ||
- | * a strong background in machine learning as well as in robotics and/or computer vision, | + | * a strong background in machine learning, AI, and robotics, |
- | * demonstrated prior achievements in some of the above areas, | + | * excellent mathematical and coding skills (C/C++, Matlab, ROS, Python), |
- | * a strong mathematical background, | + | * excellent written and oral communication skills in English, and |
- | * substantial programming experience in C++ and other languages, and | + | * enthusiasm for leading-edge research, a team spirit and independent problem-solving skills. |
- | * excellent written and oral communication skills in English. | + | |
- | Experience with PyTorch/TensorFlow/Keras and/or ROS will be a strong asset. | ||
- | Enthusiasm for leading-edge research, a team spirit and independent problem-solving skills are essential. | + | ==== How to Apply ==== |
+ | Applications must state the position(s) of interest (1, 2 or both), and must include | ||
- | ==== The University of Innsbruck, Austria ==== | + | * a letter of motivation, |
+ | * a curriculm vitae including URLs of English-language theses and dissertations, | ||
+ | * scanned transcripts (including grades) and diplomas, | ||
+ | * a list of projects you have worked on with brief descriptions of your contributions, and | ||
+ | * contact information of at least two references. | ||
- | The history of the University of Innsbruck dates back to 1669. It offers a complete set of academic curricula and currently counts 28000 students. Founded in 2001, our young Department of Computer Science is highly productive in diverse research domains, and is internationally very well connected. | + | They should be sent as PDF attachments by e-mail to both [[Justus.Piater@uibk.ac.at]] and [[Matteo.Saveriano@uibk.ac.at]]. |
- | Innsbruck is home to 35000 students who imprint a distinctive, international student atmosphere upon this lively city of 130000. Beautifully located in the Tyrolean Alps, on the Inn river and surrounded by summits of up to 2718m, Innsbruck offers outstanding opportunities and quality of life all around the year. | + | Applications must be received by **July 15, 2019**. The ideal starting date is September 1st, 2019. |
- | ==== How to Apply ==== | ||
- | Interested applicants should send a letter of motivation, a curriculum vitae including URLs of English-language theses and dissertations, scanned transcripts and diplomas, and contact information of at least two references in PDF to [[Justus.Piater@uibk.ac.at]]. | + | ==== The University of Innsbruck, Austria ==== |
- | Applications must be received by **July 11, 2018**. Starting date is October 2018 or earlier. | + | The University of Innsbruck dates back to 1669 and celebrates its 350th anniversary this year. It offers a complete set of academic curricula and currently counts 28000 students. Founded in 2001, our young Department of Computer Science is highly productive in diverse research domains, and is internationally very well connected. |
+ | |||
+ | Innsbruck is home to 35000 students who imprint a distinctive, international student atmosphere upon this lively city of 130000. Beautifully located in the Tyrolean Alps, on the Inn river and surrounded by summits of up to 2718m, Innsbruck offers outstanding opportunities and quality of life all around the year. | ||
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