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jobs [2014/08/29 09:12] – added new theses hiwi with gazebo gaming ahaidu | jobs [2018/01/22 09:25] – [Theses and Student Jobs] ahaidu | ||
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~~NOTOC~~ | ~~NOTOC~~ | ||
- | =====Theses and Jobs===== | ||
- | If you are looking for a bachelor/ | ||
+ | =====Open researcher positions===== | ||
+ | == Researcher in the area of Knowledge bases and knowledge acquisition == | ||
- | == GPU-based Parallelization of Numerical Optimization Techniques (BA/MA/HiWi)== | + | Position code A132/17. Please see [[http:// |
- | In the field of Machine Learning, numerical optimization techniques play a focal role. However, as models grow larger, traditional implementations on single-core CPUs suffer from sequential execution causing a severe slow-down. In this thesis, state-of-the-art GPU frameworks (e.g. CUDA) are to be investigated in order implement numerical optimizers that substantially profit from parallel execution. | ||
- | Requirements: | + | == Researcher with background |
- | * Skills | + | |
- | * Good programming | + | |
- | Contact: | + | Position code A133/17. Please see [[http:// |
- | == Online Learning of Markov Logic Networks for Natural-Language Understanding (MA)== | ||
- | Markov Logic Networks (MLNs) combine the expressive power of first-order logic and probabilistic graphical models. In the past, they have been successfully applied to the problem of semantically interpreting and completing natural-language instructions from the web. State-of-the-art learning techniques mostly operate in batch mode, i.e. all training instances need to be known in the beginning of the learning process. In context of this thesis, online learning methods for MLNs are to be investigated, | ||
- | Requirements: | ||
- | * Experience in Machine Learning. | ||
- | * Experience with statistical relational learning (e.g. MLNs) is helpful. | ||
- | * Good programming skills in Python. | ||
- | Contact: [[team: | ||
- | ==HiWi-Position: | + | =====Theses and Student Jobs===== |
+ | If you are looking for a bachelor/ | ||
- | In the context of the European research project RoboHow.Cog [1,2] we | + | < |
- | are investigating methods for combining multimodal sources of knowledge | + | == Lisp / CRAM support assistant |
- | The Institute | + | Technical support |
- | development | + | 8+ hours per week for up to 1 year (paid). |
- | + | ||
- | This HiWi-Position can serve as a starting point for future Bachelor' | + | |
- | + | ||
- | Tasks: | + | |
- | * Implementation of an interface | + | |
- | * Linkage of the knowledge base to the executive of the robot. | + | |
- | * Support for the scientific staff in extending and integrating components onto the robot platform PR2. | + | |
Requirements: | Requirements: | ||
- | * Studies | + | * Good programming skills |
- | * Basic skills in Artificial Intelligence | + | * Basic ROS knowledge |
- | * Optional: basic skills in Probability Theory | + | |
- | * Optional: basic skills in Machine Learning | + | |
- | * Good programming skills in Python and Java | + | |
- | Hours: 10-20 h/week | + | The student will be introduced to the CRAM framework at the beginning of the job, which is a robot programming framework written in Lisp. The student will then be responsible for assisting not familiar with the framework people, explaining them the parts they don't understand and pointing them to the relevant documentation sources. |
- | Contact: [[team:daniel_nyga|Daniel Nyga]] | + | Contact: [[team:gayane_kazhoyan|Gayane Kazhoyan]] |
+ | --></ | ||
- | [1] www.robohow.eu\\ | + | == 3D Model / Material |
- | [2] http://www.youtube.com/watch?v=0eIryyzlRwA | + | {{ : |
+ | Developing and improving 3D Models in Blender / Maya. Importing the models in Unreal Engine, where the Materials and Lightning should be improved to be close as possible to realism. | ||
- | == Depth-Adaptive Superpixels (BA/MA)== | + | Bonus: Working |
- | | + | |
- | We are currently investigating a new set of sensors (RGB-D-T), which is a combination of a kinect | + | |
- | + | ||
- | Since the current implementation of DASP is not very performant | + | |
Requirements: | Requirements: | ||
- | * Basic knowledge of image processing | + | * Experience with Blender / Maya |
- | * Good programming skills in C/C++. | + | * Knowledge of Unreal Engine material |
- | * Experience with CUDA is helpful | + | |
- | Contact: [[team: | ||
- | == Physical Simulation of Humans | + | Contact: [[team: |
- | {{ :research:human_model.png?200|}} | + | |
+ | == Unreal Engine Editor Developer | ||
+ | {{ :research:unreal_editor.png? | ||
+ | |||
+ | Creating new user interfaces (panel customization) for various internal plugins using the Unreal C++ framework [[https:// | ||
- | For tracking people, the use of particle filters is a common approach. However, the quality of those filters heavily depends on the way particles are spread. In this thesis, a library for the physical simulation of a human model is to be implemented. | ||
Requirements: | Requirements: | ||
- | * Good programming skills in C/C++ | + | * Good C++ programming skills |
- | * Optional: Experience in working | + | * Familiar with the [[https:// |
+ | * Familiar | ||
- | Contact: [[team:jan-hendrik_worch|Jan-Hendrik Worch]] | + | Contact: [[team:andrei_haidu|Andrei Haidu]] |
- | == Kitchen Activity Games in a Realistic Robotic Simulator | + | == Integrating PR2 in the Unreal Game Engine Framework |
- | {{ :research:gz_env1.png?200|}} | + | {{ :research:unreal_ros_pr2.png?100|}} |
- | Developing new activities and improving | + | Integrating |
- | under the Gazebo robotic simulator. Creating a custom GUI for the game, in order to launch new scenarios, save logs etc. | + | |
Requirements: | Requirements: | ||
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
* Basic physics/ | * Basic physics/ | ||
+ | * Basic ROS knowledge | ||
+ | * UE4 basic tutorials | ||
Contact: [[team: | Contact: [[team: | ||
+ | |||
+ | |||
+ | == Realistic Grasping using Unreal Engine (BA/ | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | The objective of the project is to implement var- | ||
+ | ious human-like grasping approaches in a game developed using [[https:// | ||
+ | |||
+ | The game consist of a household environment where a user has to execute various given tasks, such as cooking a dish, setting the table, cleaning the dishes etc. The interaction is done using various sensors to map the users hands onto the virtual hands in the game. | ||
+ | |||
+ | In order to improve the ease of manipulating objects the user should | ||
+ | be able to switch during runtime the type of grasp (pinch, power | ||
+ | grasp, precision grip etc.) he/she would like to use. | ||
+ | | ||
+ | Requirements: | ||
+ | * Good programming skills in C++ | ||
+ | * Good knowledge of the Unreal Engine API. | ||
+ | * Experience with skeletal control / animations / 3D models in Unreal Engine. | ||
+ | |||
+ | |||
+ | Contact: [[team/ |
Prof. Dr. hc. Michael Beetz PhD
Head of Institute
Contact via
Andrea Cowley
assistant to Prof. Beetz
ai-office@cs.uni-bremen.de
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