2025 Intern: Research Scientist – Human-Centered Generative AI
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2025 Intern: Research Scientist – Human-Centered Generative AI
Introduction
IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today’s most complex challenges, whether it’s discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.
Your Role and Responsibilities
IBM Research Scientists are charting the future of Artificial Intelligence, creating breakthroughs in quantum computing, discovering how blockchain will reshape the enterprise, and much more. Join a team that is dedicated to applying science to some of today’s most complex challenges, whether it’s discovering a new way for doctors to help patients, teaming with environmentalists to clean up our waterways or enabling retailers to personalize customer service.
Your Role and Responsibilities
This is for a 2025 summer internship with the following start dates: May – August or June – September for quarter system schools.
Generative AI and foundation models have introduced a paradigm shift in how we interact with AI systems. The mission of the human-centered AI teams at IBM Research is to create trustworthy, safe, and effective user experiences with generative AI. Our research focuses on (1) user perspectives of making generative AI systems safe and trustworthy by addressing new harms and risks being introduced compared to traditional AI, and (2) on designing, building, and validating novel user experiences or visualizations with generative AI systems that address the challenges of interacting with intent-based system.
We are looking for interns with a background in HCI, Data Visualization, Interaction, Visual, and Experimental Design, or similar who can help us tackle these new challenges. Topics of interest include but are not limited to new techniques and approaches for visual data exploration & analysis, novel user interfaces and visualizations for effective large language model (LLM) prompting, trust & reliance in LLM outputs, explainability of LLMs, including source attribution & rationale generation, foundation model selection and comparison for enterprise use cases, foundation model risk assessment, governance & risk mitigation techniques, understanding synergy in human-AI collaborations, and human-centered and task-specific evaluation techniques and benchmarks.
Required Technical and Professional Expertise
- Applicants should be PhD & MS students pursuing graduate studies.
- HCI, Data Visualization, Interaction, User Research, Interaction Design, Visual Design, or Experimental Design.
- Basic knowledge in Large Language Models and Generative AI.
Preferred Technical and Professional Expertise
- Qualitative and quantitative user research and user–centric design.
- Programming skills in Python, Java, C++/C, etc.
Experience publishing scientific results in technical communities such as CHI, IUI, DIS, CSCW, IEEE Vis, EuroVis, NeurIPS, ICML, ICLR, IJCAI, ACL, AAAI, or similar. - Machine learning techniques and machine learning toolkits such as PyTorch, Tensorflow, scikit–learn etc. including programming on GPUs.
- Experience in web application development and frameworks including HTML, CSS and JavaScript, JQuery, React, Flask, Node.js etc.
- Backend storage technologies such as SQL and Non–SQL databases (Postgres, MongoDB, Cloudant, ElasticSearch etc.)
- Experience in Kubernetes CI/CD tools and operators, IBM Cloud and machine learning training pipelines.
- Software engineering practices including agile techniques.
- System building/debugging/testing skills.
- Solving analytical problems using rigorous and quantitative approaches.
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