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Computational Research Assistant Jobs in Delaware

Computational Research Assistant information

What is a computational research assistant?

Computational Research Assistants are professionals who support scientific and academic research projects by applying computational methods, programming, and data analysis techniques. They often work with researchers to develop models, run simulations, analyze large datasets, and assist in the interpretation of results. Their work is essential in fields such as biology, physics, social sciences, and engineering, where complex data and computational tools are required to conduct research. Typically, they have strong skills in programming languages like Python, R, or MATLAB, and possess a background in the relevant scientific discipline.

How does a computational research assistant typically collaborate with principal investigators and other team members during a research project?

Computational Research Assistants often work closely with principal investigators (PIs), postdoctoral researchers, and other team members to design, implement, and analyze computational experiments. They are responsible for developing scripts, managing datasets, and ensuring the reproducibility of results. Regular meetings and progress updates are common, and assistants are expected to communicate findings clearly and troubleshoot technical issues collaboratively. This role requires both independent initiative and a strong team-oriented approach to meet research objectives efficiently.

What are the key skills and qualifications needed to thrive as a computational research assistant, and why are they important?

To thrive as a Computational Research Assistant, you need strong analytical skills, proficiency in programming languages like Python or R, and a background in mathematics, statistics, or computer science. Familiarity with data analysis tools, version control systems (such as Git), and experience using high-performance computing environments or relevant software is typically required. Attention to detail, problem-solving ability, and effective communication help you collaborate with research teams and interpret complex results. These skills and qualities are crucial for producing accurate, reliable research outcomes and supporting innovative scientific investigations.

What is the difference between Computational Research Assistant vs Data Analyst?

AspectComputational Research AssistantData Analyst
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fieldsBachelor's or Master's in Statistics, Data Science, or related fields
Work EnvironmentResearch labs, academic institutions, or research-focused organizationsBusiness, finance, healthcare, or marketing sectors
Employer & Industry UsageAcademic and research institutions, government agenciesCorporations, consulting firms, government agencies
Common Search & ComparisonYesNo

The Computational Research Assistant and Data Analyst roles share similarities in data handling and analytical skills, but differ mainly in their focus. Computational Research Assistants typically work in research settings, supporting scientific projects with programming and modeling, while Data Analysts focus on interpreting data to inform business decisions. Both roles require strong technical skills and relevant education, but their work environments and primary objectives differ.

Research Software Engineer, UD Institute for Data Science

University of Delaware

Newark, DE • On-site

$200K/yr

Full-time

Posted 5 days ago


University Of Delaware rating

5.7

Company rating: 5.7 out of 10

Based on 21 frontline employees who took The Breakroom Quiz

594th of 631 rated colleges and universities


Job description

Research Software Engineer, UD Institute for Data Science
Job no: 503750
College / VP Area: Research Office
Work type: Staff
Location: Newark, DE
Categories: Research & Laboratory, Full Time
Pay Grade: 31S
Context of Job:
The University of Delaware (UD) invites applications for a Research Software Engineer (RSE) to join the NSF AI Institute for Human-AI Cooperation (HAIC). The HAIC Institute (https://haicinstitute.org/) is a 5-year (2026-2031), $21.5 million, multi-institutional research initiative supported by the National Science Foundation. HAIC brings together researchers and partners to develop trustworthy AI that strengthens human expertise, shapes the future of rehabilitation and health care, and cultivates the next generation of leaders in AI. The RSE will work with HAIC researchers (from UD, University of Florida, University of Pennsylvania,Princeton University and other partner institutes) to build, validate, and maintain robust and scalable open-source software tools and cyberinfrastructure that support institute-wide research in artificial intelligence (including reinforcement learning and large vision-language models), biophysical digital twins, multimodal data processing, personalized rehabilitation, and human-AI symbiosis. The RSE will leverage high-performance computing (HPC) systems including University of Florida's HiPerGator NVIDIA SuperPod and NSF funded NAIRR resources, and work extensively with research computing professionals and NVIDIA systems engineers. Software needs include supporting reproducible research, interfacing with real-time systems and databases, and translation of AI models for a variety of deployment settings. The RSE will join a growing cohort of RSE at UD, with coordinated professional development opportunities.
This position is supported by the U.S. National Science Foundation through U.S. National Science Foundation under Cooperative Agreement No. 2433450. Continuation of this position is contingent upon performance and continued availability of these funds. Notice of non-renewal is not required.
Major Responsibilities
  • Participate as a member of a highly technical, research driven team, forging close working relationships with HAIC researchers (faculty, post-doctoral, students, and staff) across multidisciplinary working groups.
  • Provide support to HAIC researchers to use research computing hardware and software for workflows involving AI, data science, machine learning, and physics simulation, especially machine learning frameworks with interfaces for monitoring training, robust checkpointing, and validation suites.
  • Assist researchers to develop, deploy, scale, and optimize workflows that effectively and efficiently use these high-performance computing resources.
  • Utilize industry standard research software practices such as establish software version control, pipelines, institute standard testing frameworks, maintain documentation, manage public GitHub repositories to support research dissemination, applying best practices when authoring and assisting in the pursuit of modular and maintainable software codebases that accelerate scientific discovery and societal impact.
  • Help to identify appropriate hardware, software, and cyberinfrastructure platforms for different stages of research and development, including data collection, storage, and integration, along with computational-focused education and workforce development activities, assist in procurement, set-up, testing, and documentation.
  • Enable the translation of software and models toward deployment in various settings and platforms.
  • Serve as a computational liaison to research computing and IT groups at UD and partner institutions.
  • Educate, train, and advise both novice and experienced researchers regarding software engineering, shared high performance computing environments, associated software and services-adapting to individual needs and experiences-and assist in the development of workshops and other training resources.
  • Work proactively to broaden engagement between HAIC and the research cyberinfrastructure user community.
  • Perform other related duties as assigned.
  • Maintain knowledge of applicable laws and developments in state-of-the-art technology, equipment, and systems to support the institute projects.

Possible Project-Specific Technical Responsibilities:
  • Biophysical Modeling & Omniverse Integration: Assist in the development and translation of biophysical, kinematic, and musculoskeletal models (e.g., OpenSim, MuJoCo) into the NVIDIA Omniverse environment to support dynamic digital twin simulations.
  • Multimodal Data & Sensor Fusion: Implement or accelerate processing and inference algorithms for real-time multimodal data, natural language, signal, and image processing.
  • Integration of Large Language Models with Knowledge Retrieval: Assist in the use and integration of APIs, open-weight models, etc. combined with large graph databases.

Qualifications
  • Bachelor's degree in computer science, electrical and computer engineering, data science, statistics, biomedical engineering, mechanical engineering, operations research, robotics, computational neuroscience, applied mathematics, physics, or a closely-related discipline and five years of related work experience. Master's or PhD is preferred.
  • Experience with the Linux operating system and utilizing the command line interface.
    • Demonstrated ability and experience with scripting and programming languages (Bash, Python).
  • Hands-on experience with shared high-performance computing environments and workload scheduling tools (e.g., SLURM).
  • Extensive experience with version control and git, with contributions to open source repositories.
  • Ability to work effectively with researchers (both computational and non-computational) within multi-institutional teams to define, clarify, and execute requirements and goals.
  • Excellent oral and written communication skills.
  • Ability to manage multiple projects, keeping oriented to the goals and tracking details, efficiently communicating on issues and outcomes, and executing independently and in collaboration.
  • Effective organizational, interpersonal, and customer-service skills.
  • Aptitude for learning quickly and functioning in a dynamic technological environment.

Preferred Qualifications:
  • Experience with parallel computing, GPU operation (CUDA Toolkit), multi-GPU training, and distributed frameworks for machine learning (e.g. PyTorch Distributed).
  • Prior software engineering experience within AI, scientific computing, or robotics domains in industry, academia, government, or non-profit organizations, which involved architecting and managing codebases for large-scale technical projects
  • Prior contribution to computationally-focused research publications and/or software, or contribution to creating developer documentation, API guides, and descriptions of software use cases or other write-ups.
  • Experience with modern collaborative productivity environments (e.g., Slack, Trello, etc.).
  • Experience utilizing AI-assisted programming environments (e.g., GitHub Copilot, Codex, Cursor, or LLM-driven coding tools) to streamline software development, unit testing, and refactoring.
  • Course work or experience in one or more areas: AI, data science, machine learning, computer vision, signal processing, knowledge representation (e.g., knowledge graphs), information retrieval, statistics, biophysical modeling, robotics, or neuroengineering.
  • Experience developing within NVIDIA Omniverse, Isaac Sim, Isaac Gym, or custom CUDA kernels.

Notice of Non-Discrimination and Equal Opportunity
The University of Delaware does not discriminate against any person on the basis of race, color, national origin, sex, gender identity or expression, sexual orientation, genetic information, marital status, disability, religion, age, veteran status or any other characteristic protected by applicable law in its employment, educational programs and activities, admissions policies, and scholarship and loan programs as required by Title IX of the Educational Amendments of 1972, the Americans with Disabilities Act of 1990, Section 504 of the Rehabilitation Act of 1973, Title VI and VII of the Civil Rights Act of 1964, and other applicable statutes and University policies. The University of Delaware also prohibits unlawful harassment including sexual harassment and sexual violence.
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