Postdoctoral Researcher, Video Team

Jobtailor; Zug; Vor Ort; CHF 120.000 - 190.000; Vollzeit

Zusammenfassung

Jobtailor in Switzerland is seeking a PhD‑level researcher to design and implement AI/ML methods for video understanding across diverse medical modalities. You will collaborate with clinicians, data scientists, and engineers to translate advanced algorithms into robust, interpretable AI tools.

The role focuses on uncertainty quantification in model predictions and developing multi‑modal video analysis models, working with internal clinical personnel to align tools with needs.

Qualifikationen

• PhD in a quantitative field (e.g., Physics, mathematics, CS, electrical engineering) is required.
• Experience driving research in computer vision and applying CV techniques (Transformers, CNNs, RNNs, GANs).
• Proven expertise in uncertainty modeling and quantification in deep learning.
• Experience with state‑of‑the‑art video understanding (foundational models, transformers).
• Proficiency in Python or C++.
• Strong background in traditional CV applications (object detection, segmentation) and ML algorithms.

Aufgaben

• Design, implement, and evaluate AI/ML methods for video‑level understanding across medical modalities.
• Collaborate with clinicians, engineers, and data scientists to translate algorithms into robust AI tools.
• Work with internal clinical staff to understand AI tool needs and translate them into solutions.
• Lead research and development of uncertainty quantification for model predictions.
• Develop multi‑modal models for video analysis using data from multiple sources.
• Participate in cross‑functional meetings and prepare briefing reports.

Kenntnisse

Computer Vision

Uncertainty Quantification

Transformers

Python

C++

Publication Record

Collaborative Skills

Ausbildung

Ph.D. in a quantitative discipline

Tools

OpenCV

Jobbeschreibung

Responsibilities

• Design, implement, and evaluate state‑of‑the‑art AI/ML methods for video‑level understanding across diverse medical modalities.
• Collaborate closely with clinicians, engineers, and data scientists to translate advanced algorithms into robust, interpretable AI tools.
• Conceive, develop, and implement ideas with key internal clinical personnel to understand needs for AI tools.
• Lead the research and development of uncertainty quantification methods for model predictions.
• Develop advanced multi‑modal models for video analysis, integrating data from multiple sources.
• Participate in cross‑functional team meetings and drive discussions to compile briefing reports.

Requirements

• A Ph.D. degree in a quantitative discipline (e.g., Physics, mathematics, computer science, electrical engineering, or similar).
• Demonstrated experience driving research in and applying Computer Vision techniques (e.g., Transformers, CNNs, RNNs, GANs).
• Proven expertise in uncertainty model and measures development, including techniques for uncertainty quantification in deep learning.
• Demonstrated experience on state‑of‑the‑art techniques for video understanding (e.g., foundational models, transformers).
• Proficiency with one or more programming language such as Python or C++.
• Extensive experience with traditional Computer Vision applications, such as OpenCV, object detection, edge detection, image segmentation.
• Experience with machine learning algorithms, including random forest, SVM, boosting, neural networks, etc.
• Strong publication record and ability to effectively communicate technical work to a wide audience.

Core Competencies

Expertise in AI/ML methods for video‑level understanding, with a strong focus on uncertainty quantification and computer vision techniques. Proven ability to collaborate with cross‑functional teams and communicate complex technical concepts effectively.