PhD student (m,f,d) for 3 years with 29,87 hours = 75 %, (TVL E13)

Your tasks:

• The PhD student will work on developing state-of-the-art machine learning models that can scale to billions of parameters with a focus on energy efficiency. These models will use sparsity and asynchrony as core design principles to achieve energy efficiency and scalability. Neuroscience/biology can be used as inspiration to inform the development of these models. Collaborations with academic and industry groups to use bio-inspired low-energy neuromorphic hardware will be possible.
  

Your profile:

• Candidates for this post should possess:
  - A very good Master's degree in mathematics, computer science, engineering, or a related field.
  - Excellent programming skills (Python preferably).
  - Good knowledge of applied mathematics and computer science.
  - Ability to learn quickly and work independently, as well as in a team.
  
• Preferred qualifications include:
  - Interest in interdisciplinary research questions and cooperation.
  - Hands-on/research experience with deep learning.
  - Experience with machine learning frameworks such as PyTorch/Tensorflow/JAX.
  - Good communication and teamwork skills.
  - Experience or willingness to collaborate with a wide variety of interdisciplinary partners.
  

Our offerings:

• Challenging and varied tasks with a high degree of personal responsibility
  
• Qualified familiarisation
  
• Team-oriented cooperation in a committed, international and appreciative team
  
• a friendly and collegial environment
  
• Fair working hours and family-friendly working conditions
  

Additional information:

The load of teaching will be calculated according to § 3 of Lehrverpflichtungsverordnung (state of North Rhine-Westphalia).

Opportunity to do a PhD (Dr).