Scientific Collaborator in the area of deep learning and/or NLP (100%)

L'Université SUPSI recherche un Collaborateur Scientifique en apprentissage profond.

Tâches

• Développer des systèmes d'apprentissage profond pour le secteur financier.

• Collaborer avec des équipes R&D sur des projets innovants.

• Intégrer les technologies NLP dans des applications pratiques.

Compétences

• Master en ingénierie informatique ou domaine équivalent requis.

• Compétences solides en programmation Python et outils ML.

• Expérience avec les bibliothèques d'apprentissage profond.

Scientific Collaborator in the area of deep learning and/or NLP
University of Applied Sciences / Arts of Southern Switzerland - SUPSIDalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) within the Department of Innovative Technologies (DTI)

Workplace Lugano, Ticino, Switzerland Category Computer Science
Position Scientific Officer / Scientific Assistant
Occupation rate 100%
Job Start July 15, 2025, or on a mutually agreed date Published 25 June 2025 Closing Date 30 June 2025
The University of Applied Sciences and Arts of Southern Switzerland (SUPSI) invites applications for two Scientific Collaborator in the area of deep learning and/or NLP at the Dalle Molle Institute for Artificial Intelligence (IDSIA USI-SUPSI) within the Department of Innovative Technologies (DTI), located in Lugano. The degree of employment is 100%, with a contract starting on July 15, 2025, or on a mutually agreed date.

Description
The selected candidate conducts advanced research in machine learning, with a focus on natural language processing (NLP) and deep learning applications for the financial industry. The successful candidate will collaborate within an R&D team that targets the development of deep learning applications for the financial industry. The candidate will:

• Develop and implement deep learning systems in a financial industry context.
• Cooperate in R&D teams to execute projects related to the financial industry. Strong collaboration with other software engineers, researchers and industry partners.
• Collaborate with interdisciplinary teams to integrate NLP and deep learning technologies into practical applications.
• Prototype AI systems. Apply state-of-the-art techniques in deep learning, transformers, large language models, and parame-ter-efficient fine-tuning.

Requirements
• Master’s degree in computer engineering, Machine Learning, or equivalent background.
• Strong programming skills in Python and experience with modern ML tools. Experience with deep learning libraries (PyTorch/TensorFlow/ ONNX) and NumPy).
• Ability to work independently and on schedule.
• The candidate should be among the top 5 - 10 % of Master graduates of their university.

Preferred Qualifications
• Extensive experience with deep learning, particularly in the context of LLMs.
• Experience with reinforcement learning, particularly in the context of LLMs.
• Experience of work/research in a financial context is a plus but not required.
• Research experience and a PhD are a plus but not required

Knowledge of the following is a plus:
• Relational databases (e.g., MySQL, PostgreSQL) and NoSQL databases (e.g., MongoDB).
• Containerization tools (e.g., Docker).
• Expertise in CI/CD tools (e.g., Jenkins, GitLab, CircleCI).
• Microservices architecture and REST APIs.

We offer
• Fixed-term employment contract.
• No obligation to teach or participate in university management.
• Participation in cutting edge research to bring top notch research partners in the financial industry forward.
• Sufficient time to pursue research work in collaboration and publication.
• An international working environment.
• Attractive salary, in line with Swiss standards and the candidate’s experience.

Contact and Address
Applications will only be considered if submitted electronically by June 30, 2025, through the dedicated application form (https://www.supsi.ch/en/bando5030). The following documents, written in English, must be included:

• Curriculum vitae and full university transcripts.
• Motivation letter, including a brief description of past research experience and future research interests (1-2 pages).
• Names and email addresses of three reference contacts.

For further information, please contact Dr. Oleg Szehr.

Web

www.supsi.ch

www.idsia.ch

Apply online

In your application, please refer to myScience.ch and referenceJobID67589.