Assistant Research Scientist (PREP0004904)

General Description Salary: $37,725-$56,000 a year 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 Multi-Agent Consensus System for AI-Driven Antimicrobial Peptide Discovery U.S. Citizen Preferred Key responsibilities will include but are not limited to: Assist in building an ensemble of hypothesis generation agents using different large language model architectures (Claude, GPT-4, Llama variants) Assist in developing linguistic evaluation metrics to measure semantic consistency across agent outputs, including mechanism entailment, evidence overlap, and experiment design similarity Assist in creating parsers to transform STAMP's Gradient X Input explainability heatmaps into structured hypothesis cards Implementing the end-to-end pipeline from STAMP heatmaps to hypothesis cards to consensus reports Benchmarking the system against historical experimental data Contributing to scientific manuscripts and technical documentation Developing production-ready code using Python and ML/AI frameworks with version control and testing best practices Qualifications Bachelor of Science degree in Computer Science (CS), or enrolled in a Master or Ph.D. program in CS, Computational Biology, Bioinformatics, or related field Proficiency in Python programming Familiarity with machine learning frameworks (PyTorch, TensorFlow, or JAX) Familiarity with natural language processing techniques Version control (Git) and software engineering best practices Understanding of deep learning architectures and statistical analysis Willingness to work closely with wet lab researchers, biophysicists, and domain experts Genuine interest in bridging AI/ML with biomedical applications Strong communication skills for explaining computational concepts to non-CS audiences Comfort working in interdisciplinary research environments Self-motivated with strong problem-solving abilities 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: 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. #J-18808-Ljbffr Johns Hopkins University