Nokia is looking to advance connectivity and secure a brighter world through innovation in AI, quantum computing, 6G, and space communications, and is seeking a PhD intern to contribute to research and prototyping in AI/ML-based methods.
Requirements
- Knowledge of AI/ML foundations and concepts related to identifying patterns, forecasting outcomes, or evaluating system behavior.
- Demonstrable programming skills and interest in developing functional prototypes.
- Python experience preferred.
- Experience with system reliability evaluation or dynamic system modeling.
- Interest in exploring underlying causes and effects, impact evaluation, root-cause investigation, or outcome forecasting.
- Experience incorporating data-informed insights into AI-enabled guidance tools or straightforward automation workflows.
Responsibilities
- Perform research and prototyping in AI/ML-based methods, focusing on practical exploration and idea development.
- Assist in developing models to interpret relationships and anticipate system behaviors across a variety of conditions, using advanced algorithms.
- Facilitate the creation of exploratory scenarios and summarize insights that help guide team choices, potentially using AI-enhanced simulations.
- Stay current with relevant research directions, explore new possibilities, and help expand the capabilities of modern AI approaches.
- Contribute to internal demonstrations, knowledge exchange, and clear communication of outcomes to stakeholders.
- Work closely with researchers, engineers, and partner teams to advance common goals.
Other
- Actively pursuing a PhD degree in Computer Science, Engineering, Mathematics, or a related field while enrolled at an accredited US University or College.
- Strong communication abilities, including presenting work to both technical and non-technical audiences.
- A proactive approach, steady dedication to team goals, and eagerness to take on new tasks.
- Ability to work with a high degree of ownership with minimal supervision.
- Flexible and hybrid working schemes to balance study, work, and life
