Our lab is always looking for highly motivated people to join us. Feel free to contact Alex Breuer if you are interested in any of the lab’s activities.

Student Projects

Student projects are always welcome in our lab! Typically, a “student project” is your Bachelor’s or Master’s thesis. However, we are also open to all other projects! Joining us means that you become part of the lab and actively participate in the lab’s activities: We meet regularly and share our progress and thoughts, we read and discuss scientific papers, and we have a coffee break together once a day ☕.

Topics are related to the lab’s research endeavors and depend on individual preferences. Often student projects are related to classes or seminars taught by members of the lab. But you can also bring your own topic! Here is a non-exhaustive list of recent unassigned topics to get your thinking started:

  • Accelerating the Evaluation of Einsum Expressions through Matrix Engines.
  • Inter-operator Shared Memory Parallelism for Einsum Trees.
  • Efficient Quantization of Binary Tensor Contractions in Einsum Trees.
  • Guiding Compilers: Accurate Performance Models for Tensor Contractions on Modern Hardware.
  • Extension of a Domain-Specific Language for Machine Learning Workloads: Normalization, Biases, and Skip Connections.
  • Tensor Processing Primitives on the Hexagon Tensor Processor.
  • Adaptive Computing: Leveraging the AI Engine of the VCK190 Evaluation Kit.
  • Fast Tensor Contractions on the Ryzen AI Engine.
  • ADER Discontinuous Galerkin Methods for Nonlinear Hyperbolic Partial Differential Equations.

Open Positions

We are currently hiring at the Ph.D. or postdoctoral level on a case-by-case basis. You are likely to be a good match if your profile strongly overlaps with the following qualifications:

  • Master’s / Ph.D. degree in Computational and Data Science, Computer Science, Mathematics, or a related field
  • C / C++ skills and a passion for writing high quality code
  • Experience with low-level programming (assembly and machine code)
  • Experience with parallel programming and hardware architectures
  • Experience with numerical algorithms and data analysis
  • Willingness to expand your expertise into new and project-relevant areas
  • Strong verbal and written communication skills
  • Willingness to work in a dynamic and team-oriented environment
  • Experience with machine learning / deep learning frameworks and libraries
  • Python skills including interfaces to C / C++ or intermediate layers
  • Experience with good software engineering practices

We also hire highly motivated undergraduate and graduate students as teaching assistant (up to 20 hours / week).