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Scientific Collaborator in AI-enabled Precision Health
University of Applied Sciences and Arts of Southern Switzerland - SUPSI

Scientific Collaborator in AI-enabled Precision Health

2026-06-29 (Europe/Zurich)
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The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) invites applications for a Scientific Collaborator in AI-enabled Precision Health, at the Institute of Digital Technologies for Personalised Healthcare (MeDiTech) within the Department of Innovative Technologies (DTI), located in Lugano. The degree of employment is 80%, with a contract starting on 15.06.2026, or on a mutually agreed date.

The position will be supplemented by another part-time role (20%) at the Ticino Cantonal Hospital Authority (EOC) (primarily in Bellinzona).

Duties and responsibilities

Applied research activity in the field of AI-enabled precision health applications, using various algorithms to enable reuse of existing healthcare and other health data to support clinical research and clinical care. 

Software development for machine learning and data science applications (primarily in Python, including, for example, spaCy, Databricks, Keras, and PyTorch) with applications in natural language processing (NLP).

Responsible AI applications of shallow and deep machine learning algorithms in healthcare settings.

Contribution to the drafting of scientific articles for journals and conference proceedings, project documents, and internal reports.

Requirements

Essentials

  • Master’s degree in computer science, data science, informatics, software engineering, or related fields, already obtained or close to completion.
  • At least three years of relevant professional experience following the completion of studies in a related field (time spent in positions as a research assistant or doctoral candidate counts toward this experience).
  • Background in shallow and deep machine learning.
  • Strong programming skills in Python (or Java).
  • Proficiency in written and spoken English.
  • Good organizational skills, ability to work independently, and to be proactive.
  • Ability to work in a team and with colleagues and other members of the Institute and engage in scientific dialogue.

Preferred

  • Experience with Natural Language Processing (NLP) applications.
  • Experience in projects involving Python and/or Java software development, implementation and evaluation in a biomedical environment (especially healthcare / clinical).
  • Knowledge of deep learning frameworks such as PyTorch and spaCy.
  • Practical knowledge of the Italian language is preferred but not required.

What SUPSI Offers

  • Fixed-term employment contract.
  • Attractive salary, in line with Swiss standards and the candidate's experience.
  • An international working environment.
  • Participation in high-profile conferences, workshops and schools.

Application Process

Applications will only be considered if submitted electronically by 29.06.2026, through the dedicated application form. The following documents, written in English, must be included:

  • Motivation letter (1-2 pages)
  • Curriculum vitae with publications list (if any) and a link to the Master thesis
  • List of courses and grades of bachelor’s and master’s degrees (transcript of records)
  • List of (at least) two references (with e-mail addresses)

For further information, please contact: Prof. Dr. Stéphane Meystre

Incomplete applications, those submitted to incorrect addresses, or those received after the deadline will not be considered. In addition to the required application documents, further documentation (such as a criminal record certificate or a copy of an identity document) may be requested at a later stage.

Job details

Title
Scientific Collaborator in AI-enabled Precision Health
Location
Via Cantonale 2C Lugano, Switzerland
Published
2026-06-12
Application deadline
2026-06-29 23:59 (Europe/Zurich)
2026-06-29 23:59 (CET)
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The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) is one of the nine professional universities recognised by the Swiss Co...

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