Analog Devices is looking to solve problems in digitized factories, mobility, and digital healthcare by bridging the physical and digital worlds with advanced semiconductor solutions. This specific role aims to develop novel algorithms for biomedical datasets and time series analysis to drive advancements in these areas.
Requirements
- Strong machine learning background.
- Excellent abilities in mathematics and algorithm development.
- Fundamental knowledge of modeling and quick prototyping skills.
- Proficiency in Python.
- Familiarity with C++, C.
Responsibilities
- Work with biomedical, unstandardized data from collection to downstream tasks (clustering/classification).
- Quickly prototype solutions and proof of concepts for uncharted application domains where solutions might exist in the literature.
- Communicate with domain experts and stay abreast of the state of the art to develop novel algorithms that provide a market edge.
- Apply strong understanding of signal processing and machine learning models to develop solutions from literature or novel approaches to meet performance measures.
- Support hardware and software teams with algorithmic solutions to ensure data quality measurement, comparison, and improvement.
Other
- Recent college graduate (PhD)
- Individual contributor
- Interest to dig deep and have the breadth
- Real-world experience with biomedical datasets and/or time series, including pre-processing, algorithm development, and validation
- Solution-oriented, capable of working with multiple modalities, and eager to tackle uncharted areas.
- Required Travel: Yes, 10% of the time
- PhD in Electrical Engineering, Mathematics, Computer Science or a relevant field
