The team you'll be part of
The AI Research Lab at Bell Labs Solutions Research invites applications for a research scientist position (fixed term 7 months) in machine learning. The Lab has a long tradition of excellence in research and currently consists of 80 staff members with expertise in algorithmic and computing sciences, stochastic networks, information theory and machine learning. Candidates will have a strong and proven background in fields such as deep learning or privacy-preserving machine learning, and a natural interest in innovatively applying fundamental tools and methods in focused problem areas. The candidate would be working in a team consisting of machine learning scientists and engineers, including experts in deep learning and wireless communications.
The successful applicant will conduct high-quality research in machine learning (ML) and its applications, for example in Wireless ML domain.
Candidates must either hold a PhD in machine learning or data science, computer science, applied mathematics (e.g. numerical analysis or statistical methods), or related fields, or be finalizing their PhD in near future. Previous experience in, for example, wireless communications, deep learning, or machine learning optimization is considered as an advantage. A proven track record in a related field is preferable.
For further information regarding this position contact
mikko.honkala@nokia-bell-labs.com
When applying for the position through the website, please note that we mainly consider your resume, preferably in PDF format. Other fields may be filled briefly.
Are you passionate about solving problems? As part of our team, you will:
Perform research in machine learning methods and applications, e.g., in wireless AI domain. Follow machine learning and related fields to be familiar with, and to improve over, current state of the art. Produce quantifiable demonstrations of your research. Jointly with other members of the team, develop new machine learning methods and design new models. Implement the solutions as computer programs for evaluation. Train models with large amounts of data. Actively participate in new and challenging application areas within wireless AI and participate in team efforts.