Student research assistant for implementing neural network benchmarks
We are looking for a student research assistant to help us implement different machine learning benchmark models, starting as soon as possible.
You will be tasked with implementing different machine learning benchmark models in PyTorch based on papers. The models to be implemented include XGBoost-, FNN-, CNN- and transformer-based models. We will provide you with guidance for the implementation, but independent work in general is required. The workload consists of 4 hours per week on average during the semester. We handle working time flexibly so that you can take time to prepare for exams or fulfill other study obligations. The salary will be CHF 30.70/h.
- Current master's student
- Languages: German or English
- Very experienced with PyTorch
- (Ideally) research experience
- Ability to understand papers and to implement models based on these
ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity and attractive offers and benefits.
Working, teaching and research at ETH Zurichscience and technology. We are renowned for our excellent education,
cutting-edge fundamental research and direct transfer of new knowledge
into society. Over 30,000 people from more than 120 countries find our
university to be a place that promotes independent thinking and an
environment that inspires excellence. Located in the heart of Europe,
yet forging connections all over the world, we work together to
develop solutions for the global challenges of today and tomorrow.
