Postdoctoral Fellow (PREP0004606)

Johns Hopkins University; Baltimore (MD); On-site; USD 70,000 - 90,000; Full time

Benefits offered by this job

Health and career support

Retirement benefits

Comprehensive rewards package

Job summary

Johns Hopkins University is seeking a PREP Research Associate in Baltimore, Maryland. This role involves collaborating on scientific research projects linked to indoor air quality modeling using AI to support CONTAM model development. Ideal candidates will possess a Ph.D. in Mechanical Engineering and be familiar with programming languages such as C, C#, Python, or Java.

The position emphasizes the use of existing CONTAM software and APIs to enhance modeling efforts. Strong communication skills are required to facilitate cooperative efforts with other researchers and contributors.

Qualifications

• Ph.D. in Mechanical Engineering or a related field.
• Familiarity with various programming languages.
• Strong communication skills necessary for collaboration.

Responsibilities

• Gain familiarity with CONTAM IAQ modeling software.
• Understand the newly developed CONTAM APIs.
• Use CONTAM APIs to generate and modify project files.
• Develop AI-based methods for CONTAM building models.

Skills

Ph.D. in Mechanical Engineering or related field

Familiarity with programming languages (C, C#, Python, Java)

Familiarity with Git DevOps and CI/CD pipelines

Experience in developing agent-based AI

Strong oral and written communication skills

Education

Ph.D. in Mechanical Engineering or a related field

Job description

PREP Research Associate

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

Indoor Air Quality Modeling - Artificial Intelligence to Support CONTAM Model Development

Work will entail

Identifying and developing AI-based methods to generate and exercise CONTAM building models.

Key Responsibilities

• Gain familiarity with the use of existing CONTAM IAQ modeling software
• Gain a strong understanding of the newly developed CONTAM APIs
• Apply CONTAM APIs to generate, modify, and perform simulations on CONTAM Project files
• Develop AI-based methods to generate CONTAM building models

Qualifications

• Ph.D. in Mechanical Engineering, or a related field
• Familiarity with multiple programming languages, e.g., C, C#, Python, or Java
• Familiarity with Git DevOps and CI/CD pipelines
• Familiarity with developing and applying agent-based AI
• Strong oral and written communication skills

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.