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Riverside, California
Posted: 09-May-26
Location: Gaithersburg, Maryland
Type: Full-time
Salary: 62,000.00 - 84,000.00
Categories:
Internal Number: A-186516-26
General Description
PREP Research Associate
This position is part of the National Institute of Standards (NIST) Professional Research Experience (PREP) program. NIST recognizes that its research staff may wish to collaborate with researchers at academic institutions on specific projects of mutual interest, thus requires that such institutions must be the recipient of a PREP award. The PREP program requires 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.
Research Title
Machine Learning for Neutron Reflectometry
The work will entail:
Neutron reflectometry (NR) is one of the techniques of choice to fill the data gap for disease-relevant proteins or peptides at cell membranes under pharmaceutically relevant conditions. A NR-based innovative measurement approach, called the Reflectometry-driven Optimization And Discovery of Membrane Active Peptides (ROADMAP), is currently being developed at NIST to create an autonomous biomolecule design infrastructure. Antimicrobial peptides (AMP), which can efficiently disrupt bacteria membrane upon interaction with the lipid bilayer, are the focus of ROADMAP.
The successful candidate will design and implement the AI component of ROADMAP, which will determine the sequence of NR measurements leading to a comprehensive dataset within the experimental time and resource constraints. The main tasks of the recipient will be: to develop data structures that capture AMP properties, multimodal NR observables and experimental conditions; to select appropriate AI architectures; to validate the resulting AI framework on AMPs of interest in the context of ROADMAP.
Key responsibilities will include but are not limited to:
§ Assess state-of-the-art AI models for computer-aided drug design, drug screening and biochemical property prediction.
§ Define data structures for the representation of AMPs and their targets. Specific focus should be on natural language processing (NLP)-based approaches and graph convolutional neural networks.
§ Design and implement AI models for the prediction of peptide antimicrobial properties and assess their prediction accuracy.
§ Design and implement AI models for the generation of novel peptides with optimal properties.
§ Study the peptide representation associated with the implemented AI models, define metrics to characterize the prediction performance.
§ Provide guidance for the next batch of NR measurements, which will yield additional training data in an iterative fashion.
§ Define AI-specific metrics to assess the diversity of the AI-generated peptides, validate the efficient exploration of the antimicrobial peptide space in collaboration with the stakeholders.
§ Write manuscripts to disseminate the work.
Qualifications
§ A Ph.D. in computer science, computational biology, statistics, mathematics, or a related field.
§ 5+ years of experience in machine learning with application to biochemistry.
§ 5+ years of experience with state-of-the-art generative and predictive AI tools in the context of drug design and bioinformatics, with strongly preferred specific experience in the space of antimicrobial peptides.
§ 5+ years of experience in natural language processing.
§ 5+ experience with Pytorch and Tensorflow platforms for ML modeling.
§ 5+ years of experience with popular platforms for AI modeling, such as PyTorch and TensorFlow.
§ 5+ years of experience with the PyTorch Geometric platform for building and evaluating Graph Neural Networks.
§ Working knowledge of popular platforms for processing and analyzing molecular sequences, such as RDkit and pysmiles.
§ 5+ years of experience in developing prototypes of tools for data analysis in the bioinformatics domain.
§ Strong oral and written communication skills.
US citizenship 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
- Personal Interest
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 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.
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 characteristic. 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 that are irrelevant to the program involved.
Pre-Employment Information
If you are interested in applying for employment with The 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 jhurecruitment@jhu.edu. For TTY users, call via Maryland Relay or dial 711. For more information about workplace accommodations or accessibility at Johns Hopkins University, please visit accessibility.jhu.edu.
Background Checks
The successful candidate(s) for this position will be subject to a pre-employment background check including education verification.
EEO is the Law:
https://www.eeoc.gov/sites/default/files/2023-06/22-088_EEOC_KnowYourRights6.12ScreenRdr.pdf
Vaccine Requirements
Johns Hopkins University strongly encourages, but no longer requires, at least one dose of the COVID-19 vaccine. The COVID-19 vaccine does not apply to positions located in the State of Florida. We still require all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the COVID and flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry. 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. 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 employees 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.
