Master’s thesis , Document AI and Knowledge Extraction
Date de publication :
20 août 2024Taux d'activité :
100%- Lieu de travail :Zürich
Master’s thesis , Document AI and Knowledge Extraction | |
Published | 21 May 2024 |
Workplace | Zurich, Zurich region, Switzerland |
Category | Computer Science |
Position | Trainee |
Master’s thesis Document AI and Knowledge ExtractionRef. 2023_018 About us The IBM Research Laboratory is located in Ruschlikon close to Zurich. This creates a fantastic opportunity for highly motivated Student to join our unique research-corporate environment for a Master Thesis, Semester Project or Internship.
As an intern in our group, you will be working on a large scale platform that has ingested 500M documents and you will have the ability to apply the new model developments at scale. Furthermore, you will collaborate with experienced Research Scientists and AI Software Engineers that will lead and help you to successfully complete the challenges of the proposed task and have access to HPC and Cloud infrastructure equipped with recent variants of GPUs and many other resources and tools to perform the work. Minimum Qualifications Bachelor’s degree in computer science, computer vision or a related technical field, including equivalent practical experience Experience in software development with Python Proficient working in Unix/Linux environments Team player, self-motivated with a passion for technology and innovationPreferred Qualifications Experience in one or more of the following: REST APIs, machine learning, deep learning, algorithms and data structures, test automation, distributed computing, CI/CD Practical experience with Machine Learning / Deep Learning frameworks such as PyTorch 3+ years of proved programming experience in Python (or equivalent C/C++ experience) Independent worker with the ability to effectively operate with flexibility in a fast-paced, constantly evolving team environmentDiversity IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable all genders to strike the desired balance between their professional development and their personal lives. How to apply If you are interested to apply for this position, please submit your application through the link below. | |
In your application, please refer to myScience.ch and referenceJobID64441. |