Praktikum oder Thesis im Bereich TECIA1/ Deep Reinforcement Learning in simulation in Friedrichshafen, Baden-Württemberg, Germany

Airbus



Airbus Defence and Space GmbH

Airbus is a global leader in aeronautics, space and related services. In 2018 it generated revenues of € 64 billion and employed a workforce of around 134,000. Airbus offers the most comprehensive range of passenger airliners. Airbus is also a European leader providing tanker, combat, transport and mission aircraft, as well as one of the world's leading space companies. In helicopters, Airbus provides the most efficient civil and military rotorcraft solutions worldwide.

Our people work with passion and determination to make the world a more connected, safer and smarter place. Taking pride in our work, we draw on each other's expertise and experience to achieve excellence. Our diversity and teamwork culture propel us to accomplish the extraordinary - on the ground, in the sky and in space.

Job Description

Internship/Thesis: Deep Reinforcement Learning in simulation

Description of the department

The department 'National Studies Germany' (TECIA1) at Airbus Defence and Space GmbH in Friedrichshafen is heavily involved in artificial intelligence related activities within Airbus. As study driven and therefore also research oriented department we are looking forward to explore the possibilities of artificial intelligence in the military domain.

Topic

Your mission will be to support and setup innovative machine learning environments to implement and use state of the art reinforcement learning algorithms. Your internship will cope with the following topics:

  • Setup Machine Learning environment based on Google Tensorflow with Python on Google Cloud / Cloud ML or on a local cluster architecture
  • Support the preparation of appropriate training data based on simulation data
  • Design, train and evaluate different neural network architectures and algorithms (e.g. PPO2, DQN, MADDPG)

As an intern you will learn about

Your mission will be to support and setup innovative machine learning environments to implement and use state of the art reinforcement learning algorithms. Your internship will cope with the following topics:Setup Machine Learning environment based on Google Tensorflow with Python on Google Cloud / Cloud ML or on a local cluster architectureSupport the preparation of appropriate training data based on simulation dataDesign, train and evaluate different neural network architectures and algorithms (e.g. PPO2, DQN, MADDPG)

Your tasks

  • Development of state of the art reinforcement learning (RL) environments
  • Evaluation of RL algorithms
  • Setup of appropriate training architecture (e.g. server/cluster, MPI etc.)
  • Support existing RL topics and introduce new perspectives/innovative ideas
  • Software skills (programming languages) and technical skills

We are looking for an extremely self-motivated person, who is proactively contributing to all relevant topics and is keen in evaluating and improving different neural network architectures and designs. We are looking for someone who loves to be challenged and who wants to go the extra mile.

  • The duration of your internship should be at least 3 months, and we would prefer having someone for 6 months or to directly continue with a bachelor or master thesis. Please note that the start date of the internship shall be as soon as possible. You should have an IT background bringing with you basic knowledge in Deep Learning/Deep Reinforcement Learning and Tensorflow as well as good practical experiences in Python.


This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Companys success, reputation and sustainable growth.

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.
Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

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