Johns Hopkins University
Salary: $40,000-$50,000 a year
Status: Full Time
PREP Research Associate
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST recognizes that research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, and therefore requires that such institutions must be the recipient of a PREP award. The PREP program brings together staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
The position is for a graduate student level researcher or recent PhD graduate experienced in and interested in applied data science to work jointly with mathematicians and experimentalists at NIST to study forensic chemometrics and uncertainty quantification in identification and classification in mass spectrometry. A goal of this work is to develop improved classification and identification algorithms in analytical chemistry and incorporate uncertainty quantification into models to provide useful information. The role will be highly interdisciplinary, requiring regular communication between mathematicians working on modeling these devices and experimentalists taking measurements and producing data.
Key Responsibilities & Qualifications
Implementing optimized calculations to study AI classification algorithms.
Assessing uncertainty in classification of experimental data.
Computationally testing mathematical models relating to uncertainty quantification.
Significant software development (most likely Python).
Disseminating results through posters and seminars at meetings.
Ensuring that all results, findings, data, and software are correctly archived and transmitted through appropriate channels.
Either completed master’s degree or PhD in data science or a related field.
Minimum of 1 year of experience conducting data science research.
Significant coursework in mathematics, statistics, and/or computer science.
Knowledge of or interest in acquiring knowledge of chemistry and chemometrics methods.
Familiarity with larger computational and AI/ML software packages.
Ability to program in a modern computational language such as Python.
Program Overview The PREP program is a 5‑year cooperative agreement between NIST laboratories and participating universities to establish collaborative research relationships in disciplines including biochemistry, chemistry, computer science, engineering, materials science, mathematics, physics, and statistics.
Application Instructions Please upload the following with your application:
Please limit your CV to 3 pages only and include a valid email address for your contact information. Your resume will not be considered if the following information is included on your CV/resume.
CV/Resume (limited to 3 pages, include a valid email address.)
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)
#J-18808-Ljbffr
Status: Full Time
PREP Research Associate
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience (PREP) program. NIST recognizes that research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, and therefore requires that such institutions must be the recipient of a PREP award. The PREP program brings together staff from a wide range of backgrounds to work on scientific research in many areas. Employees in this position will perform technical work that underpins the scientific research of the collaboration.
The position is for a graduate student level researcher or recent PhD graduate experienced in and interested in applied data science to work jointly with mathematicians and experimentalists at NIST to study forensic chemometrics and uncertainty quantification in identification and classification in mass spectrometry. A goal of this work is to develop improved classification and identification algorithms in analytical chemistry and incorporate uncertainty quantification into models to provide useful information. The role will be highly interdisciplinary, requiring regular communication between mathematicians working on modeling these devices and experimentalists taking measurements and producing data.
Key Responsibilities & Qualifications
Implementing optimized calculations to study AI classification algorithms.
Assessing uncertainty in classification of experimental data.
Computationally testing mathematical models relating to uncertainty quantification.
Significant software development (most likely Python).
Disseminating results through posters and seminars at meetings.
Ensuring that all results, findings, data, and software are correctly archived and transmitted through appropriate channels.
Either completed master’s degree or PhD in data science or a related field.
Minimum of 1 year of experience conducting data science research.
Significant coursework in mathematics, statistics, and/or computer science.
Knowledge of or interest in acquiring knowledge of chemistry and chemometrics methods.
Familiarity with larger computational and AI/ML software packages.
Ability to program in a modern computational language such as Python.
Program Overview The PREP program is a 5‑year cooperative agreement between NIST laboratories and participating universities to establish collaborative research relationships in disciplines including biochemistry, chemistry, computer science, engineering, materials science, mathematics, physics, and statistics.
Application Instructions Please upload the following with your application:
Please limit your CV to 3 pages only and include a valid email address for your contact information. Your resume will not be considered if the following information is included on your CV/resume.
CV/Resume (limited to 3 pages, include a valid email address.)
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)
#J-18808-Ljbffr