Senior NLP Data Scientist

• Working on projects requiring expertise with LLM-based and NLP methods with collaborators from the academic and public sectors.
• Supervise and collaborate with students at different levels, providing guidance and supervision.
• Engage with diverse stakeholders, including researchers across various domains and other professionals.
• Prepare scientific publications for top-tier machine learning and domain conferences and journals.
• Evaluating project proposals., Interested in creating tools that will promote and universalize the usage of modern ML methodologies? Come and join our team!

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

• Motivation letter (max 2 pages)
• CV (including publication list)
• Contact details for 2 to 3 references
• Other relevant documents: electronic copies of diplomas, transcripts, certificates, links to code repositories, and/or a portfolio of projects

Further information about the Swiss Data Science Center can be found on our website. Examples of projects carried out by the Research team can be found here.

Questions regarding the position should be directed to luis.salamanca@sdsc.ethz.ch (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.

Do you have experience in Research?, Do you have a Master's degree?, The ideal candidate holds a PhD in NLP and has experience with large language models and/or other foundation models. In particular, relevant experience includes training or fine-tuning (language) models of different sizes, familiarity with the characteristics of main language models and their domain applicability, and experience with large-scale data projects. For large language models, beyond prompt engineering techniques, familiarity with parameter-efficient fine-tuning, agentic methods, advanced usages, and transfer methodologies would be of particular interest. We expect the candidate to be proficient in Python and PyTorch, and familiar with Hugging Face Transformers, NLTK, LLM environments, tools for agentic AI, etc. Also, the candidate should have demonstrated research excellence through publications in relevant venues.

We value profiles with proven experience in interdisciplinary projects and environments in which developments are guided by domain research questions. We are thus seeking candidates with a strong curiosity about learning from other non-technical disciplines and proficient in presenting methods and results to non-technical audiences.

Professional Development:

• Opportunities to publish contributions to research projects in high-impact journals
• Possibility to travel and present work in international venues
• Involvement in supervision of MSc and BSc students

100%, Zurich, fixed-term The Swiss Data Science Center (SDSC) is a national research infrastructure in data science and artificial intelligence (AI) within the ETH domain, with EPFL and ETH Zurich as founding partners. Its mandate is to support academic labs, hospitals, industry and public sector stakeholders, including cantonal and federal administrations, through their entire data science journey, from the collection and management of data to machine learning, AI, and industrialization. With a large multidisciplinary team of professionals across three locations (Lausanne, Zurich, Villigen), the SDSC provides expertise and services across domains such as health and biomedical sciences, energy and sustainability, climate and environment, and large-scale scientific infrastructure. The candidate will be integrated into a dynamic and rich environment, with people from different fields and expertise, and will be part of SDSC's Research team. The Research team at the SDSC comprises more than 35 data scientists, seeking to apply novel AI/ML methods to solve real-world problems in the academic and public sectors. See for an idea of some of our academic research collaborations.