Student research assistant for implementing neural network benchmarks

10%-20%, Zurich, fixed-term

We are looking for a student research assistant to help us implement different machine learning benchmark models, starting as soon as possible.

Job description

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.

Profile

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

Workplace

We offer

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 Zurich

We value diversity

In line with our values, ETH Zurich encourages an inclusive culture. We promote equality of opportunity, value diversity and nurture a working and learning environment in which the rights and dignity of all our staff and students are respected. Visit our Equal Opportunities and Diversity website to find out how we ensure a fair and open environment that allows everyone to grow and flourish.

Curious? So are we.

We look forward to receiving your online application with the following documents:

A short motivation letter highlighting your research experience and/or your experience with PyTorch
CV
Transcript of records

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the Technology Marketing chair can be found on our website. Questions regarding the position should be directed to Daniel Schoess, email dschoess@ethz.ch (no applications).

For recruitment services the GTC of ETH Zurich apply.

About ETH Zürich

ETH Zurich is one of the world’s leading universities specialising in science 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.

Curious? So are we.

We look forward to receiving your online application with the following documents:

A short motivation letter highlighting your research experience and/or your experience with PyTorch
CV
Transcript of records

Please note that we exclusively accept applications submitted through our online application portal. Applications via email or postal services will not be considered.

Further information about the Technology Marketing chair can be found on our website. Questions regarding the position should be directed to Daniel Schoess, email dschoess@ethz.ch (no applications).

For recruitment services the GTC of ETH Zurich apply.

Apply online now