Researcher with PhD in the area of Privacy Preserving Data Processing

Researcher with PhD in the area of Privacy Preserving Data Processing

The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) has opened a full time (100%) position for a Researcher with PhD in the area of Privacy Preserving Data Processing at the Department of Innovative Technologies (DTI) located in Lugano, within theInstitute of Information Systems and Networking (ISIN) . Contract start 1st July 2026 or date to be agreed upon.

Scope and purpose of the position

The purpose of this position is to support research and development (R&D) activities focused on designing novel solutions for privacy-preserving machine learning, with a particular focus on Large Language Models (LLMs). The selected candidate will contribute to the design and implementation of privacy-enhancing technologies tailored to transformer-based architectures. This role involves close collaboration with interdisciplinary teams, including academic researchers, software engineers, and industry partners, to help translate cutting‑edge research into practical solutions for privacy-preserving inference and fine-tuning of LLMs.

Responsibilities and activities

The selected candidate will join research groups focused on the development of privacy-preserving data-driven solutions, with specific focus on privacy-enhancing technologies and privacy-preserving machine learning technologies.

• Contribute to the design and implementation of privacy-preserving technologies, specifically tailored to transformer-based architectures and LLMs, with emphasis on secure training and inference.
• Collaborate with interdisciplinary teams, including NLP experts, software engineers, and academic/industrial partners, to translate cutting‑edge research into practical applications.
• Support research and development activities aimed at advancing privacy-preserving machine learning techniques, evaluating their effectiveness, scalability, and compliance.
• Develop and test software prototypes of privacy-preserving systems, contributing to the integration of the proposed solutions into real platforms or technological demonstrators.

Requirements

The ideal candidate will meet the following essential requirements:

• PhD in Computer Science, Data Science, Machine Learning, or related fields.
• Proven experience with privacy-enhancing technologies and their application to privacy-preserving machine learning.
• Strong experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and data science tools (e.g., NumPy, Pandas, Scikit-learn).
• Proficient in programming, especially in Python, with familiarity in version control systems (e.g., Git).
• Solid mathematical background, including linear algebra, probability theory, optimization, and cryptography.
• In-depth understanding of machine learning algorithms, with a focus on transformer-based models.
• Ability to work independently and manage project timelines and deliverables.
• Strong publication record in fields such as privacy, machine learning, and/or natural language processing.
• Demonstrated ability to collaborate effectively in interdisciplinary and international teams.

We offer

• A fixed-term contract, with the possibility of renewal.
• Participation in cutting edge research with national industrial partners.
• Attractive salary, in line with Swiss standards and the candidate's experience.
• Mixed position between research and high-tech development.

Candidates must submit the following documents in English:

• Curriculum vitae with a list of publications and (if available) a link to the PhD thesis
• List of exams and corresponding grades obtained during the Bachelor's and Master's degrees
• List of two references (with e-mail addresses)
• A motivation letter, including a brief description of past research experience and future interests (1-2 pages)

In addition to the documents to be sent at the time of online application, additional documentation (criminal record, copy of an identity document) may be requested at a later date.

Applications will be considered only if submitted electronically by 17 May 2026 , through the appropriate form. Applications that are incomplete, submitted to other addresses, or submitted beyond the deadline, will not be accepted.