Internship - System Analytics and Predictive Maintenance

Company: 
Palo Alto Research Center (PARC, a Xerox Company)
Date Posted: 
February 12, 2020

PARC Internship in System Analytics, Anomaly Characterization, System Modeling, Monitoring, Prognostics, Diagnostics, and Planning - Palo Alto, CA, USA

PARC's System Sciences Lab (SSL) is unlike any organization in the world. Combine the best of an esteemed research organization, a top-notch university, an entrepreneurial startup, and a premiere technology company and you get SSL, a team that melds its world-class innovation chops with a focus on researching and developing real world applications that have market potential. Research in SSL focuses on embedded sensing, artificial intelligence, modeling, design, condition management, machine learning, control, planning, optimization, and high-performance analytics for a variety of cyber-physical system applications serving industry leaders in product lifecycle management, computer-aided design, manufacturing, transportation, energy, and aerospace/defense sectors. The lab's focus extends beyond invention: the team creates new business options and opportunities.

We are working on innovative analytics projects within SSL's Analytics for Condition Evaluation of Systems (ACES) research area to monitor the health condition of devices and systems, detect/characterize system anomalies, model component/device failures, enable accurate inferences about their state, deliver recommendations for decision support, and plan missions with device fleets. The analytics will focus on processing/fusion of multiple sources of data from devices/systems, building models, and machine learning approaches, which allow insight generation and accurate actionable recommendations.

The ACES research area is a growing group of researchers within SSL, with world-class strengths in sensing, diagnostics, prognostics, predictive maintenance, data analytics, controls, planning, and physics-based modeling of complex engineering systems. The work in ACES covers a broad range of technology maturity, from abstract algorithm formulation all the way down to embedded software implementation on physical hardware platforms that span various application domains such as manufacturing, energy, grid, heavy machinery, unmanned aerial vehicles, civil infrastructure, and intelligent transportation systems. These technologies are being developed in collaboration with major government agencies and have been successfully demonstrated/deployed for leading Global 1000 clients. More details at https://www.parc.com/technologies/condition-based-maintenance/

As one of the most prolific innovation centers in the world with a rich legacy of pioneering technology breakthroughs, PARC offers an exceptional internship experience. Considered valuable members of our community, interns are fully integrated into the daily activities of PARC's highly collaborative, multidisciplinary culture. For more information on the PARC internship program visit http://www.parc.com/internship

Responsibilities

Assist in designing, developing, and delivering innovative approaches, algorithms, methods, and models as needed for state monitoring, prediction, planning, and recommendations
Survey and implement recent system analytics approaches and algorithms
Develop and implement parameter tuning and model selection algorithm
Implement efficient data preprocessing and wrangling software for given sensor data sets
Implement backend system such as server and database for proof-of-concept demonstration
Document/present findings and results

Requirements

Master's/Ph.D. students who have completed at least 2 years of graduate studies in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, or related fields
Background in sensing, system modeling, monitoring, prognostics, diagnostics, machine learning, signal processing, planning, autonomy, or optimization
Hands-on software and algorithm development
Programming experience in Python, R, C/C++ Modelica, or Matlab
Hands on experience in machine learning package (e.g. Scikit-learn, Keras, NIMBLE), open-source database (e.g., Influxdb, Cassandra), and/or sensors is a plus
Experience with prognostics and health management (PHM) concepts and tools is a plus

Benefits

Intern benefits include 401K, Relocation and Holidays.

About PARC

PARC, a Xerox company, is in the Business of Breakthroughs®. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. We create new business options, accelerate time to market, augment internal capabilities, and reduce risk for our clients.

Since its inception, PARC has pioneered many technology platforms – from the Ethernet and laser printing to the GUI and ubiquitous computing – and has enabled the creation of many industries. Incorporated as an independent, wholly owned subsidiary of Xerox in 2002, PARC today continues the research that enables breakthroughs for our clients' businesses.

PARC is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color, religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. People with disabilities who need a reasonable accommodation to apply or compete for employment with PARC should contact PARC Human Resources.

  
 
 
 

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