Academic Associate UAS in Machine Learning (80‑100%) • Collaborateur ou collaboratrice scientifique HES en Machine Learning (80‑100%)
Institution: Institut Informatique HES‑SO Valais‑Wallis
This role offers a unique opportunity to work on cutting‑edge machine‑learning techniques, primarily focused on deep learning for multimodal alignment (2D‑3D) and speech processing. The position may also include teaching responsibilities.
Position Description
Conduct research and development in machine‑learning, focusing on deep learning and multimodal alignment (2D‑3D).
Participate in regular project meetings and contribute to advancing the academic community at the HEI.
Collaborate with faculty members and other researchers on research and innovation projects.
Participate in teaching activities, including tutoring and grading.
Selection Criteria
Master’s degree or higher in computer science, machine learning or a related field.
Proven experience in machine‑learning; experience in deep learning and computer vision is a strong advantage.
Excellent programming skills in Python and data‑intensive programming; good knowledge of PyTorch is a strong advantage.
Strong analytical and problem‑solving abilities.
Effective communication skills and ability to work both collaboratively and independently.
Proficiency in English (min. B2 level in both written and spoken communication); operational French (approximately B1 level) is an advantage for informal daily interactions and participation in teaching activities.
Employment Details
Employment type: Full‑time.
Seniority level: Mid‑Senior level.
Job function: Education and Training.
Industries: IT Services and IT Consulting.
Duration: 24 months.
Place of work: Sion, hybrid work possible.
Starting date: 1 February 2026 or to be determined.
Activity level: 80‑100%.
Contact & Application
For further information, please contact Prof. Louis Lettry (louis.lettry@hevs.ch) or Prof. Gregory Mermoud (gregory.mermoud@hevs.ch).
Please submit your complete application documents (CV, motivation letter, diplomas and certificates) by 15 January 2026, via the “Apply” button. Only online applications will be considered.
#J-18808-Ljbffr