Student Research Assistants in Computer Science & Law 10%-20%

ETH Zürich; Zürich; Vor Ort; CHF 24.000 - 32.000; Vollzeit

Benefits dieser Stelle

Office in Zurich city center

English working language

Independent technical implementation

Zusammenfassung

ETH Zürich's Center for Law & Economics invites student researchers to join projects at the intersection of data science, AI, law, and economics. You will work on web data collection, NLP, and LLM pipelines, or on computer vision and visual data analysis, contributing to interdisciplinary research with a focus on reproducible workflows.

You will collaborate with legal and economics scholars, using Python, NLP, and ML tools, with Linux-based deployments and Git/version control, while dedicating

Qualifikationen

• Experience with Python, web scraping, and SQL is required.
• Familiarity with NLP, LLM pipelines, and Docker is a plus.
• Experience with Linux and Git is essential.

Aufgaben

• Develop web data pipelines to scrape, store, validate, and reproduce data.
• Interact with LLM APIs and manage research code on Linux VMs.
• Explore computer vision methods, embeddings, clustering, and multimodal models.

Kenntnisse

Python

Web scraping

SQL

Linux

Git

NLP

LLM pipelines

Tools

Docker

PyTorch

OpenCV

Vector similarity search

Jobbeschreibung

The Center for Law & Economics at ETH Zurich conducts empirical and experimental research in law & economics and AI & law. At the Center, Professor Stefan Bechtold is looking for student research assistants with a background in computer science, data science, or related fields to support interdisciplinary research projects at the intersection of data science, artificial intelligence, law, and economics.

Project background

Our research uses computational methods to study legal, economic, and social-science questions at scale. Many of our projects focus on innovation, competition, copyright, privacy, or regulating digital platforms & AI systems. One group of projects involves collecting and analyzing content from websites. This includes scraping structured and unstructured web content, storing and managing large datasets, applying statistical and natural-language processing methods, and developing LLM-based pipelines for empirical legal research. These projects require reliable data-collection infrastructure and reproducible workflows that can process large amounts of text and web data. A second group of projects focuses on the computational analysis of visual content. We work with large collections of images and associated metadata. These projects involve methods such as image embeddings, similarity search, clustering, computer vision, and multimodal AI. Across both areas, research assistants are encouraged not only to implement predefined tasks but also to help identify, test, and evaluate suitable computational approaches.

Job description

Depending on your background and interests, your work may focus primarily on one of two areas:

Web Data, NLP & LLM Pipelines

• scraping and extracting web content and maintaining reproducible data-collection pipelines
• interacting with LLM APIs (e.g., OpenAI, OpenRouter)
• storing, querying, cleaning, and validating data using SQL/PostgreSQL
• applying NLP, statistical methods, and LLM-based approaches to textual data
• deploying and maintaining research code on Linux virtual machines

Computer Vision & Visual Data Analysis

• processing and analyzing large image collections and associated metadata
• using image embeddings, similarity search, clustering, and multimodal models
• identifying identical, similar, or related images across large datasets
• evaluating computational methods and visualizing resulting patterns

Profile

• You are a registered student at a university in Zurich or nearby
• For the Web Data, NLP & LLM profile, you have experience with Python, web scraping, and SQL. Experience with NLP, statistical methods, LLM pipelines, LLM APIs, and/or Docker is a plus
• For the Computer Vision & Visual Data Analysis profile, you have experience with Python, computer vision, image processing, or machine learning. Experience with PyTorch, image embeddings, vision-language models, OpenCV, or vector similarity search is a plus.
• Across both profiles, experience with Linux and Git is essential, and experience with web interface and data visualization development to present results in interactive, accessible formats is a plus
• You are at a stage of your studies where, during the semester, you can dedicate 10 to 15 hours per week (potentially more outside of the semester)
• You are interested in designing and conducting interdisciplinary research projects in collaboration with a team of legal and economics scholars
• We value strong problem-solving skills, clean and reliable code, independence, and careful attention to data quality and reproducibility. Your ability to quickly understand and work with unfamiliar codebases, together with a strong willingness to learn new tools and techniques, will help you in this job. You do not need experience with every technology listed above. Knowledge of law, economics, or legal research is also not required

We offer

• We are an interdisciplinary research group at the intersection of law, economics, and data science working on large collaborative projects on regulating the digital economy. You will work closely with our team while having substantial independence in the technical implementation of your work.
• This position offers exposure to real-world, large-scale research datasets, flexibility to contribute ideas on methods and implementation, and opportunities to build computational infrastructures used in academic research.
• Our offices are in the city center of Zurich, our working language is English.

> Working, teaching and research at ETH Zurich

We value diversity and sustainability

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. Sustainability is a core value for us - we are consistently working towards a climate-neutral future.

Curious? So are we.

We look forward to receiving your online application until October 4, 2026, with the following documents:

• a cover letter (2 pages max; please describe your relevant background and motivation in the letter),
• your CV, and
• your university transcript with exam grades.

Further information about our research group can be found at the Intellectual Property Group (Bechtold) and the website. Questions regarding the position should be directed to Prof. Stefan Bechtold ([e-mail]) (no applications).

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

We would like to point out that the pre-selection is carried out by the responsible recruiters and not by artificial intelligence.