Job Description for PhD Student (f/m/d) for Thesis Topic: NLP for Visual-to-Language models

We are developing algorithms which, based on camera, lidar and radar sensor data, can understand complex driving scenarios (e.g. crowded multi-lane highways, inner cities), anticipate the behavior of other road users (e.g. pedestrian crossing the road, vehicle changing the lane or taking a turn) and finally make safe and comfortable driving decisions.

Are you (almost) finished with your Master's degree and want to pursue a PhD? Do you want to bridge the gap between academics and industry and apply your scientific expertise to real challenges in the area of automated and autonomous driving?

Your Role

With the growing amount of data in different areas it is becoming more and more challenging to identify the desired data in a potentially large pool of data. Thus, techniques are required to capture the semantics of data (e.g., images or point clouds) in an automated way.

In this thesis a method should be developed to represent the semantics of images of street scenes (e.g., a pedestrian crossing in front of car, overtaking maneuvers, etc.) in a way that it is possible to query that information. Natural Language Processing (NLP) techniques shall be used for this and the algorithm shall also be integrated in an existing data warehousing solution. Thus, the focus shall not only be on retrieving the best possible selection of images but also on efficient implementation.

Your Profile

• You hold a master’s degree in Computer Science, Engineering or similar

• You have practical experience with NLP and at least one ML framework like Tensorflow, Keras, Caffe, PyTorch, fast.ai etc

• You can program self-reliant in Python and/or C++

• You have good English skills (German skills would be a plus)

• You are looking for a challenging task, bring a high level of self-motivation and like to be part of a team

We Offer

• Funding for a 3-year full-time Ph.D. scholarship in cooperation with a university

• Opportunity to work on state-of-the-art machine learning solutions in a research-oriented environment

• Hands-on work with real-world data

• A strong global team of highly educated machine learning engineers to contribute and support you

Interested?

• Great! Please apply and include your CV and (important!) a grade overview.

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