Internship - Decentralized Data Assimilation for Large Scale Systems
Mitsubishi Electric Research Laboratories · Cambridge, MA · 2 mo ago
Information TechnologyVolunteer
Purpose
The purpose of this internship is to conduct research on decentralized data assimilation for multi-physical and multi-component systems governed by large-scale nonlinear differential-algebraic equations (DAEs).
About the role
This internship is open to senior Ph.D. students in mechanical, electrical, chemical engineering, or related fields.
Responsibilities
- Conduct research on decentralized data assimilation for multi-physical and multi-component systems governed by large-scale nonlinear differential-algebraic equations (DAEs).
- Study, develop, and efficiently implement data assimilation algorithms for such complex systems.
- Work with one or more of the following areas: nonlinear estimation and control, Bayesian methods, machine learning, graph theory, and optimization.
Requirements
- Demonstrated expertise in one or more of the following areas: nonlinear estimation and control, Bayesian methods, machine learning, graph theory, and optimization, through peer-reviewed publications or equivalent experience.
- Strong background in one or more of the following areas: nonlinear estimation and control, Bayesian methods, machine learning, graph theory, and optimization.
- Proficiency in Julia or Python programming.
Qualifications
- Senior Ph.D. student in mechanical, electrical, chemical engineering, or related fields.
Skills
- Experience with large-scale nonlinear differential-algebraic equations (DAEs).
- Knowledge of data assimilation algorithms.
- Ability to work independently and collaboratively.
Benefits
- Relocation stipend.
- Covered travel to and from MERL.
- Monthly Charlie Card for local commuting.
- Weekly social gatherings and professional development opportunities.
- Health insurance coverage after a 90-day waiting period.
- Immigration support for qualified candidates.
Pay
The pay range for this internship position will be 6-8K per month.
Schedule
The internship is typically 3 months in duration, with a flexible start date.