Research ProgrammerPosition DetailsRecruitment/Posting Title - Research ProgrammerDepartment - Quantitative Biomedicine InstSalary Details - $120,000 - $130,000Offer Information - The final salary offer may be determined by several factors, including, but not limited to, the candidate's qualifications, experience, and expertise, and availability of department or grant funds to support the position. We also take into consideration market benchmarks, if and when appropriate, and internal equity to ensure fair compensation relative to the university's broader compensation structure. We are committed to offering competitive and flexible compensation packages to attract and retain top talent.Benefits - Rutgers provides a comprehensive benefits package to eligible employees. The specific benefits vary based on the position and may include: Medical, prescription drug, and dental coverage Paid vacation, holidays, and various leave programs Competitive retirement benefits, including defined contribution plans and voluntary tax-deferred savings options Employee and dependent educational benefits (when applicable) Life insurance coverage Employee discount programsPosting Summary - The Rutgers Artificial Intelligence and Data Science (RAD) Collaboratory is seeking one or more Research Programmers to support leveraging modern Machine Learning (ML) and Deep Learning (DL) techniques by Rutgers faculty, postdoctoral fellows, and students. The ideal candidate will have a strong ML/DL and cyberinfrastructure (CI) background and a willingness to contribute to interdisciplinary research across diverse basic and applied science and engineering domains.
Responsibilities will include: Design, develop, and deploy ML/DL algorithms for domain science and engineering fields Support RAD Collaboratory research on national cyberinfrastructure (e.g., ACCESS, NAIRR, and DOE supercomputers) or cloud environments (e.g., AWS, GCP, and Azure) Support application of ML/DL/CI techniques across topics and domains Deliver training on ML/DL/CI techniques and best practices to a broad range of researchers Stay at the forefront of new ML/DL techniques and ML/DL systems that support science and engineering research Co-author peer-reviewed interdisciplinary research publications Contribute to funding applications from external sources (e.g., NSF, NIH)Position Status - Full TimePosting Number - 25FA0745Posting Open Date - 08/01/2025QualificationsMinimum Education and Experience - Ph.D. in computer science, engineering, or other related research fields with a strong background in applied ML/DL in interdisciplinary research.
Experience working with ML/DL platforms and algorithms. Track record of working with domain experts, researchers, and stakeholders to support diverse science and engineering applications.Certifications/LicensesRequired Knowledge, Skills, and Abilities - Experience with DL frameworks such as PyTorch, DeepSpeed, Accelerate, or Megatron-LM Experience with large language model (LLM) techniques such as supervised fine-tuning, retrieval augmented generation, and in-context learning Advanced Statistical Analysis: Proficiency in advanced statistical techniques and probability theory GPU Programming: Experience with GPU programming and optimization for ML models, utilizing frameworks, like CUDA or OpenCL Experience with applied computer vision, such as convolutional neural networks and vision transformers is preferred Experience in deploying open-source and open-data DL projects at scale and job management with SLURM or PBS is preferred Knowledge of software engineering and MLOps (e.g., CI/CD workflow) is preferred Familiarity with scientific or ML workflows is preferred Training or tutorial experience for domain scientists Ability to learn and adapt to new technologies Excellent writing and verbal communication skillsPreferred QualificationsEquipment UtilizedPhysical Demands and Work Environment - Individual will work onsite at RCSB PDB located at Rutgers Busch Science Campus (Piscataway, NJ)Overview - The RAD Collaboratory was recently launched by the Office of the Rutgers New Brunswick Chancellor as a Chancellor-reporting Signature Initiative (CSI) that aligns with Rutgers–New Brunswick Academic Master Plan. This initiative serves as a hub for data science, artificial intelligence, student programming, and community engagement.