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jobs [2014/07/11 11:50] – [Theses and Jobs] jworch | jobs [2018/01/22 09:23] – [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 and the integration of probabilistic methods in AI, which enable intelligent robots | + | 8+ hours per week for up to 1 year (paid). |
- | This HiWi-Position can serve as a starting point for future Bachelor' | + | Requirements: |
+ | * Good programming skills in Common Lisp | ||
+ | * Basic ROS knowledge | ||
+ | |||
+ | 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 | ||
+ | |||
+ | Contact: [[team: | ||
+ | --></ | ||
+ | |||
+ | == 3D Model / Material / Lightning Developer (Student Job / HiWi)== | ||
+ | {{ : | ||
+ | |||
+ | 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. | ||
- | Tasks: | + | Bonus: Working with state of the art 3D Scanners [[https:// |
- | * Implementation | + | |
- | * Linkage of the knowledge base to the executive of the robot. | + | |
- | * Support | + | |
Requirements: | Requirements: | ||
- | * Studies in Computer Science (Bachelor' | + | * Experience with Blender / Maya |
- | * Basic skills in Artificial Intelligence | + | * Knowledge of Unreal Engine material / lightning editing |
- | * Optional: basic skills in Probability Theory | + | |
- | * Optional: basic skills in Machine Learning | + | |
- | * Good programming skills in Python and Java | + | |
- | Hours: 10-20 h/week | ||
- | Contact: [[team: | ||
- | [1] www.robohow.eu\\ | + | Contact: |
- | [2] http:// | + | |
+ | == Unreal Engine Editor (GUI) Developer (Student Job / HiWi)== | ||
+ | {{ : | ||
- | == Depth-Adaptive Superpixels | + | Creating user interfaces |
- | | + | |
- | We are currently investigating a new set of sensors (RGB-D-T), which is a combination of a kinect with a thermal image camera. Within this project we want to enhance the Depth-Adaptive Superpixels (DASP) to make use of the thermal sensor data. Depth-Adaptive Superpixels oversegment an image taking into account the depth value of each pixel. | + | |
- | Since the current implementation of DASP is not very performant for high resolution images, there are several options for doing a project in this field like reimplementing DASP using CUDA, investigating how thermal data can be integrated, ... | ||
Requirements: | Requirements: | ||
- | | + | * Good C++ programming skills |
- | | + | * Familiar with [[https:// |
- | * Experience | + | * Familiar |
- | Contact: [[team:jan-hendrik_worch|Jan-Hendrik Worch]] | + | Contact: [[team:andrei_haidu|Andrei Haidu]] |
+ | == Integrating PR2 in the Unreal Game Engine Framework (BA/ | ||
+ | {{ : | ||
- | == Depth-Adaptive Superpixels (BA/MA)== | + | Integrating the [[https:// |
- | | + | |
- | + | ||
- | For tracking people, | + | |
Requirements: | Requirements: | ||
* Good programming skills in C/C++ | * Good programming skills in C/C++ | ||
- | * Optional: Experience | + | * Basic physics/ |
+ | * Basic ROS knowledge | ||
+ | * UE4 basic tutorials | ||
+ | |||
+ | Contact: [[team: | ||
+ | |||
+ | |||
+ | == Realistic Grasping using Unreal Engine (BA/ | ||
+ | |||
+ | {{ : | ||
+ | |||
+ | The objective of the project is to implement var- | ||
+ | ious human-like grasping approaches | ||
+ | |||
+ | The game consist of a household environment where a user has to execute various given tasks, | ||
- | Contact: [[team: | + | 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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