Expires on: 05/05/2024
Runtime information such as metrics, traces, and logs is currently outside the scope of the IDE. It is possible to develop, design, and refactor a system in an IDE, but only a few plugins make it possible to consider the available runtime information during the development process in the IDE. Developers can use various observability tools to receive alerts and create dashboards that can impact development, but getting feedback from runtime information directly in the IDE is difficult.
The goal of this project is to study how we can process runtime and observability data to improve the development process in the IDE. There are a lot of different research directions, such as anomaly detection, improving code generation and refactoring, creating smart tips for developers, and developing debugging and profiling assistants. The solution can be either ML or non-ML.
This PhD position is part of the AI for Software Engineering lab (AI4SE), a collaboration between JetBrains and Delft University of Technology. Hence, the prospective PhD student will also work closely with researchers and developers of JetBrains. More information is available at https://lp.jetbrains.com/research/ai-for-se/. (edited)
Requirements
We are seeking a candidate who meets the following criteria:
- Holds a Master’s degree in computer science with a focus on Software Engineering, Software Testing, and Machine Learning.
- Possesses a strong background in programming using Python, Java, or Kotlin, with a potential portfolio demonstrating contributions to open-source projects.
- Possesses some expertise with static or dynamic analysis or with telemetry data.
- Shows proficiency in writing comprehensive documents and seamlessly integrating production-level software.
- Demonstrates excellent verbal and written English skills.
Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2770 per month in the first year to € 3539 in the fourth year.