Research Engineer Piping System

3 weeks ago


Cambridge, United States Banzan International Group Corporation Full time

Job Title: Research Engineer Piping System

Division: MathEarth IoT Group

Department: Research & Development

Summary:

We are seeking a qualified individual for the role of Research Engineer tasked with spearheading the design and execution of pressure transient experiments within a water pipeline laboratory. The successful candidate will play a pivotal role in refining algorithms for anomaly detection within water distribution networks, collaborating closely with cross-functional teams to implement innovative solutions effectively.

Responsibilities

Designing a water pipeline laboratory for conducting pressure transient experiments.

Developing and conducting experiments to assess, validate, and optimize algorithms for pressure transient detection and localization.

Testing and enhancing algorithms for identifying and localizing anomaly events in water distribution networks, focusing on areas such as leaks/bursts, pressure variations, and system irregularities using monitoring data.

Staying abreast of the latest advancements in academic literature to explore innovative approaches for addressing real-world challenges within water distribution pipe networks.

Collaborating closely with the R&D team, data engineers, and software engineers to seamlessly integrate algorithms into operational systems, ensuring practical applicability and efficiency.

Qualifications:

Proficiency in fluid mechanics and fluid behaviors in pipes

Knowledge and experience in fluid pipe laboratory operations and experiments.

Passion for applying innovative methods to solve real-world problems, with a self-motivated and research-oriented mindset.

Excellent communication skills and a strong teamwork mentality.

A Master's degree (M.A./M.S.) in mechanical engineering or a related field, accompanied by at least 2 years of research or industrial experience.

Preferred Qualifications:

Knowledge of wireless sensor monitoring networks.

Proven experience in data science and machine learning.

Proficiency in data science and programming tools such as Python, MATLAB, or R.

Familiarity with signal processing techniques including time-frequency analysis, FFT, wavelet analysis, adaptive filtering, noise reduction, etc.

A Doctorate of Philosophy in a related field.


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