Kariera

Research Scientist (Deep learning / Machine learning)

Job Responsibilities:

  • Design, implement and maintain modules related to traffic prediction, accidents prediction, and driver behaviour models (among others);
  • Work on predictive vehicle routing, predictive capacitated electric vehicle charging, image processing to dynamically allocate vehicles to trips, traffic prediction, accident prediction, driver behaviour analysis. ;
  • The subject areas include, but are not limited to: Reinforcement learning, Deep learning and adversarial machine learning, Knowledge representation and (symbolic) reasoning, Control theory, Operational research, Multiagent systems, Algorithmic game theory and mechanism design. ;

Education and Experience:

  • PhD in machine learning or related field, with research published in to platforms, such as ICML, NIPS, AAAI, IJCAI or their equivalent;
  • Solid background in statistical approaches or other latest approaches and methodologies in AI;
  • Strong programming skills in at least one object-oriented programming language (Python, C++, Java, Scala, etc.) ;

Core Skills:

  • Experience in machine learning algorithm implementation, as well as the ability to make use of open source tools to further develop models;
  • Experience with a deep learning framework, such as TensorFlow or PyTorch;
  • Ability to develop prototypes by manipulating and analysing complex, high-volume, high-dimensional data from varying sources;
  • Eager to learn new algorithms, new application areas and new tools;
  • Ability to communicate and collaborate with other researchers and engineers, excellent written and oral communication skill;
  • Strong programming skills in Python with an emphasis on data structures and algorithms;

Preferred:

  • Deep academic or industry expertise (post PhD 5+ years) in one or more related areas;
  • An active contributor to the relevant international research communities, and able to create and act as a champion of a specific sub-topic and particular technology or application;
  • Hands-on experience in applying machine learning techniques to solve real-world transportation problems;
  • Experience in working with cloud platforms.

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