Senior Research Scientist (PREP0004257)

The Chronicle Of Higher Education, Inc.

Gaithersburg (MD)

On-site

USD 115,500 - 126,000

Full time

14 days+

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Benefits offered by this job

Health and life benefits
Career support
Retirement package

Job summary

The Chronicle Of Higher Education, Inc. is seeking a PREP Research Associate to support NIST collaborations. The role requires significant research experience in additive manufacturing and expertise in laser applications.

Key responsibilities include analyzing data from AM processes, developing anomaly detection methods, and presenting results at various platforms. A PhD in Mechanical Engineering or a closely related field is required. A strong background in machine learning and deep learning is preferred.

Qualifications

  • Eight or more years of relevant research experience in additive manufacturing.
  • Experience with high-speed visible and thermographic imaging techniques.
  • Strong oral and written communication skills.

Responsibilities

  • Analyze and pre-process data from NIST AM testbeds.
  • Develop methods for process anomaly detection.
  • Assist in organizing workshops to disseminate research.

Skills

Laser-based metal additive manufacturing processes
Machine learning and deep learning algorithms
In-situ measurements
FPGA architectures
Technical communication

Education

PhD in Mechanical Engineering or related field

Tools

CAD
FPGA programming or integration

Job description

Salary

$115,500 - $126,000

Position Title

PREP Research Associate

Description

This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program and works to support collaborations with academic researchers. Employees in this role perform technical work that underpins the scientific research of the NIST‑University partnership, including the development and improvement of an open‑architecture Additive Manufacturing (AM) platform.

Research Title

Open‑Architecture Additive Manufacturing Platform Development

Key Responsibilities
  • Analyzing, pre‑processing, and formatting data generated from NIST AM testbeds and comparing these data with datasets from other NIST systems and external collaborators.
  • Developing methods to fuse multimodality data from AM process monitoring for process anomaly detection and quality assessment.
  • Presenting research results at internal and external meetings and assisting in organizing workshops to disseminate NIST open‑architecture AM platforms.
  • Providing assistance with CAD, digital signal processing hardware and algorithms, and prototyping new measurement systems on the AM testbeds.
  • Assisting in deploying real‑time feedback control capabilities on AMMT and LPDT as a retrofit solution for existing AM systems.
  • Providing technical support for planning, execution, and data‑collection phases of experiments conducted on the AMMT at NIST.
  • Offering end‑to‑end support for synchrotron‑based research, including logistics of LPDT transport and setup at external facilities and post‑experimental analysis of complex X‑ray diffraction data.
Qualifications
  • PhD in Mechanical Engineering, Information Science, or a closely related field.
  • Eight or more years of relevant research experience in additive manufacturing or closely related advanced manufacturing systems.
  • Demonstrated expertise in laser‑based metal additive manufacturing processes.
  • Extensive experience with in‑situ measurements and process monitoring applied to advanced manufacturing processes; experience with high‑speed visible and thermographic imaging techniques preferred.
  • Strong background and demonstrated experience working with and developing applied machine learning and deep learning algorithms, with experience in machine vision and image processing applications preferred.
  • Experience with AM system control frameworks and familiarity with industry AM communication protocols.
  • Experience with FPGA‑based sensing systems, including familiarity with FPGA architectures and at least one FPGA programming or integration workflow.
  • Demonstrated professional service and leadership experience, including organizing workshops, seminars, conferences, or hackathon‑style technical events.
  • Strong oral and written communication skills, supported by a record of peer‑reviewed publications and presentations to technical and multidisciplinary audiences.
U.S. Citizen Preferred

Preferred if the candidate is a U.S. citizen.

Equal Employment Opportunity Statement

The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. The University does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity, or expression, veteran status, or other legally protected characteristics. The University is committed to providing qualified individuals access to all academic and employment programs, benefits, and activities on the basis of demonstrated ability, performance, and merit without regard to personal factors or demographic characteristics that are irrelevant to the program involved.

Total Rewards

Johns Hopkins offers a total rewards package that supports employees’ health, life, career, and retirement. More information can be found at https://hr.jhu.edu/benefits-worklife/.

EEO is the Law

https://www.eeoc.gov/employees-job-applicants

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