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- Assistant Research Scientist (PREP0004828)
Description
Salary: $50,000-$80,000 a year
Status: Full Time
PREP Research Associate
CHIPS Funded Project.
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Title:
Research Engineer
The work will entail:
The candidate will join a multidisciplinary team of scientists working to advance nondestructive defect detection metrology for advanced semiconductor packaging by developing reference artifacts and benchmark datasets. The candidate will contribute to various aspects of the project, including, but not limited to, designing CAD models, running X-ray computed tomography (XCT) simulations, performing XCT reconstructions to generate datasets, preparing samples for FIB/SEM, and nanofabrication. The candidate will develop a Python script or package to automate these processes. Additionally, the candidate will use a team-developed generative modeling process to produce 3D models with seeded defects. The datasets will be used to evaluate defect detection and image segmentation algorithms, including those based on deep learning principles. The incumbent will analyze the resulting measurements, perform image processing, and extract meaningful information to support the research goals outlined in the experiment plan. They will organize the measured and analyzed datasets for publication, communicate with the team, and share the results at conferences and in publications.
U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
§ Design 3D models for simulation, run XCT simulations, carry out XCT reconstruction, and execute image analysis.
§ Organize and prepare data sets for publication.
§ Presenting results at internal meetings and occasional meetings with external stakeholders.
§ Publish results in journals and present results at conferences.
Qualifications
§ A master's degree in physics, engineering, or a related discipline.
§ Experience with XCT measurements, reconstruction, and image analysis. Experience with XCT simulation is a plus.
§ Experience in writing Python scripts. Familiarity with automating or controlling other software, tools, or processes through APIs, inter-process communication, or similar methods is a plus.
§ Experience in writing Python packages or with other programming languages like C++ or Tcl/Tk is a plus.
§ Experience with implementing deep learning-based image segmentation processes is a plus.
§ Experience with sample preparation (mechanical polishing, focused ion beam) or scanning electron microscopy imaging is a plus.
§ Strong oral and written communication skills.
§ Able to quickly learn and adapt to new fields or techniques
- Knowledge of software engineering for AI applications
- Knowledge of mathematical probability and statistics and optimization methods
- Knowledge of machine learning including supervised and unsupervised learning, deep learning, and model evaluation
- Knowledge of dataset biases, and labeling issues
- Knowledge of AI model building
- Knowledge of translating operational needs into solvable AI problems
- US Citizens Preferred
Application Instructions
Please upload the following with your application:
- CV/Resume
*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.
- Self portraits
- Phone number
- Home address/Country
- Citizenship status
- Languages spoken
- Sex/Gender
Privacy Act Statement
Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate the administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated. By applying to a CHIPS-funded PREP opportunity, you also acknowledge that participation in the project requires signing a Non-Disclosure Agreement (NDA) prior to beginning any work.
Salary Range
The referenced salary range represents the minimum and maximum salaries for this position and is based on Johns Hopkins University's good faith belief at the time of posting. Not all candidates will be eligible for the upper end of the salary range. The actual compensation offered to the selected candidate may vary and will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, internal equity, market conditions, education/training and other factors, as reasonably determined by the University.
Total Rewards
Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits-worklife/.
Equal Opportunity Employer
The Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, 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.
Pre-Employment Information
If you are interested in applying for employment with Johns Hopkins University and require special assistance or accommodation during any part of the pre-employment process, please contact the HR Business Services Office at [email protected]. For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations at Johns Hopkins University for disabilities, medical conditions (including medical conditions related to pregnancy or childbirth), accessibility, or religious reasons, please visit accessibility.jhu.edu.
Background Checks
After receiving a conditional offer, the successful candidate(s) for this position will be subject to a pre-employment background check including education verification. When deciding whether a candidate's conviction history is job-disqualifying, the University considers the nature and gravity of the offense, the time that has passed since the conviction, and the nature of the job being sought.
EEO is the Law
https://www.eeoc.gov/employees-job-applicants
Vaccine Requirements
Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. This change does not apply to the School of Medicine (SOM). SOM hires must be fully vaccinated with an FDA COVID-19 vaccination and provide proof of vaccination status. We still require all faculty, staff, and students to receive the seasonal flu vaccine.
Exceptions to the seasonal flu vaccine or COVID-19 vaccine (for SOM) requirement(s) may be provided to individuals with sincerely held religious beliefs or medical conditions that preclude them from receiving the vaccine. Requests for an exception must be submitted to the JHU vaccination registry. For additional information, applicants for SOM positions should visit https://www.hopkinsmedicine.org/coronavirus/covid-19-vaccine/ and all other JHU applicants should visit https://covidinfo.jhu.edu/health-safety/covid-vaccination-information/.
The following additional vaccine requirements may apply, depending upon your campus. Please contact the hiring department for more information.
The pre-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2) MMR vaccines; two (2) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre-employment physical exam except for those candidates who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.
