Research Engineer (f/m/div) for Statistical 3D Model of Quadrupeds
Indexed description
Department website ∶ https://is.mpg.de/oslab/
The Project
Horses are one of the most beloved animals. They are beautiful in shape and motion, they have been used for carrying people, goods, for helping in farming, for racing, and also for therapy. We are interested in capturing horse motion from motion capture data, with the goal of building marker-less motion capture systems for horses. We are collaborating with the Swedish University of Agricultural Sciences and IMATI-CNR in developing a system for the markerless motion capture of horses. Our approach is based on creating a highly realistic 3D articulated model of horses from data. To this goal, we need to capture partial 3D scans of real animals and register them to a predefined horse template. Doing this enables us to model the shape of real horses and the shape variability across a range of individuals with different characteristics. In this research context, we are looking for a talented research engineer to pursue the project.
The Optics and Sensing Laboratory at the Max Planck Institute for Intelligent Systems in Tübingen has an open position for a
Research Engineer (f/m/div) for Statistical 3D Model of Quadrupeds
to join the ongoing research efforts in the development of statistical 3D models of Quadrupeds.
Roles & Responsibilities
- Investigation, implementation and evaluation of potential model improvements, for example ∶ skeleton/joint paradigms, shape space encoding variations, pose dependent deformations, etc.
- Conceptualization and development of model evaluation procedures, including quantitative and qualitative metrics.
- Development of various Minimum-Viable-Product pipelines, including image/video mesh recovery models and use-case applications (e.g. body conformation scoring from model outputs).
- Enhancement of the process for re-training and establishing a continuous learning pipeline.
- Improvement of an established robust method for registering 3D parametric model templates to cleaned 3D scans.
- Project management ∶ definition and evaluation of projects' steps and directions.
- Experience with 3D parametric body models (i.e. SMPL/MANO/ATLAS/VAREN, etc.)
- Experience in Computational Geometry, Computer Vision and Deep Learning
- Accepted publications in one of these fields is a big advantage
- Good programming skills in Python or C++; PyTorch (or similar) experience
- Project management experience and the ability to work independently in dynamic environments
- Experience in one or more of the following ∶ Point-cloud libraries, OpenCV, 3D rendering pipelines and deep ‑ learning frameworks
- Good oral and written communication skills in English
- Enjoyment for collaborative work and multidisciplinary projects
- A minimum of a Master’s degree is required
- Experience writing production level code is a plus
The Max Planck Society is committed to increasing the number of individuals with disabilities in its workforce and therefore encourages applications from such qualified individuals. The Max Planck Society strives for gender equality and diversity. Furthermore, the Max Planck Society seeks to increase the number of women in its workforce in those areas where they are underrepresented and therefore explicitly encourages women to apply.
The position is available as of now and will be open until filled or no longer needed.
Application
Any questions regarding the position should be forwarded to Keiko Kitagawa at [email protected] and Dr. Senya Polikovsky at [email protected].
Candidates should send their ∶
- Curriculum Vitae
- References
- GitHub account showing us your programming skills
- Two-page response to the following ∶
- Motivation and why you are a good fit, and how this position contributes to your career aspirations.
- Please provide your thoughts on a) what makes your code production ready, or b) what would need to be addressed to do so.
- The existing (public) state of the art 3D parametric model for horses (VAREN) sees limited success when modelling small horses (e.g. Shetland Ponies). What is your intuition as to why this may be and (briefly) how you would address this.
- As a footnote, briefly write how AI was used in answering the questions and how you verified the AI output.
Please send the requested documents as a single application package, in a single PDF file, to the application portal. Applications without these documents including the letter will not be considered.
If you prefer to send a hardcopy application, you may do so. Please send it to ∶ MPI-IS, Keiko Kitagawa, Max-Planck-Ring 4, 72076 Tübingen.
Closing date for applications
The posting is open until filled or no longer needed.
Max Planck Institute for Intelligent Systems
Max-Planck-Ring 4
72076 Tübingen
is.mpg.de
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