Research Programmer

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 StatusFull Time Posting Number25FA0745Posting Open Date 08/01/2025 Posting Close Date QualificationsMinimum 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/Licenses: Required 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 theoryGPU 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 skills

Preferred Qualifications: Equipment Utilized

Physical Demands and Work Environment: Individual will work onsite at RCSBPDB 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. Statement Posting Details Special Instructions to Applicants Quick Link to Posting CampusRutgers University-New Brunswick Home Location CampusBusch (RU-New Brunswick) City PiscatawayStateNJLocation Details Pre-employment Screenings All offers of employment are contingent upon successful completion of all pre-employment screenings.

Immunization Requirements: Under Policy 100.3.1 Immunization Policy for Covered Individuals, if employment will commence during Flu Season, Rutgers University may require certain prospective employees to provide proof that they are vaccinated against Seasonal Influenza for the current Flu Season, unless the University has granted the individual a medical or religious exemption. Additional infection control and safety policies may apply. Prospective employees should speak with their hiring manager to determine which policies apply to the role or position for which they are applying. Failure to provide proof of vaccination for any required vaccines or obtain a medical or religious exemption from the University will result in rescission of a candidate's offer of employment or disciplinary action up to and including termination.

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