PhD UX Research Intern - Summer 2026

📍 Job Overview

Job Title: PhD UX Research Intern - Summer 2026

Company: Ipsos

Location: New York, NY, United States

Job Type: Internship

Category: User Experience (UX) Research / Human-Computer Interaction (HCI)

Date Posted: February 20, 2026

Experience Level: PhD Student (with preference for 3+ years UX research/design experience)

Remote Status: Hybrid

🚀 Role Summary

• This 10-12 week internship focuses on evaluating AI-powered user research tools and their impact on the future of work within a leading global research organization.

• The role involves in-depth analysis of emerging AI tools, understanding their application in research workflows, and contributing to the development of novel research methodologies for academic and industry audiences.

• Successful candidates will leverage their PhD-level research skills to assess usability, ethical considerations, and the transformative potential of AI in user experience research practices.

• This position offers practical experience in a hybrid work environment, fostering collaboration with experienced researchers and contributing to Ipsos' commitment to user-centered design and innovation.

📝 Enhancement Note: While the core of the role is UX Research, the emphasis on AI-powered tools, research workflows, and the future of work suggests a strong intersection with operational efficiency and the strategic application of technology within a research context. This role is ideal for a PhD candidate looking to bridge academic rigor with applied industry research, particularly in the evolving landscape of AI in research operations.

📈 Primary Responsibilities

• Conduct a comprehensive landscape analysis of AI-powered user research tools and platforms, identifying key players, functionalities, and emerging trends.

• Design, plan, and execute research studies to evaluate the usability, efficacy, and impact of selected AI tools on real-world research projects.

• Analyze how AI technologies are transforming traditional research practices, including data collection, qualitative and quantitative analysis, and the communication of research findings.

• Collaborate closely with experienced UX researchers and cross-functional teams to contribute to the development of innovative research methodologies that effectively leverage AI capabilities.

• Synthesize research findings into actionable reports, compelling presentations, and potential academic publications suitable for both industry stakeholders and the broader scientific community.

• Engage in in-depth interviews with technical audiences, including developers, to understand complex computing topics and translate these insights into practical research applications.

• Contribute to exploring the future of work for user researchers, examining how AI is reshaping required skills, expertise, and potential career paths within the field.

📝 Enhancement Note: The responsibilities highlight a significant focus on process evaluation and innovation within the research domain. The "research workflows" and "novel research methods development" aspects are critical for operations-minded candidates, indicating a need to not only use tools but also to understand and improve the underlying processes of research execution.

🎓 Skills & Qualifications

Education:

• Actively enrolled in a graduate PhD program in Human-Computer Interaction (HCI), Cognitive Science, Information Sciences, Digital Media, or a closely related field.

Experience:

• 3+ years of experience in user experience research or design is highly preferred, demonstrating practical application of research principles.

• Proven ability to conduct in-depth interviews with developers and technical audiences, effectively gathering insights on complex computing topics.

Required Skills:

• UX Research Methodologies: Deep understanding and practical application of qualitative and quantitative UX research methods.

• AI Tool Evaluation: Ability to critically assess the capabilities, limitations, and ethical considerations of AI-powered research tools.

• Research Design & Execution: Proficiency in designing and conducting user studies, from planning to data analysis and synthesis.

• Academic Publication: Experience in writing and presenting research for top-tier academic conferences.

• Technical Acumen: Ability to understand and discuss complex computing topics with technical experts.

• Independent Work Ethic: Strong initiative, resourcefulness, and ability to work autonomously with minimal supervision.

• Time Management & Prioritization: Effective skills in managing multiple tasks and deadlines in a dynamic research environment.

Preferred Skills:

• Experience with programming and developing computational tools.

• Familiarity with AI/ML concepts and their application in research.

• Experience in translating technical findings into actionable business insights for industry audiences.

• Familiarity with data analysis and visualization tools.

📝 Enhancement Note: The emphasis on "computational topics translation," "programming," and "computational tool development" suggests that candidates with a technical background or a strong interest in the intersection of UX and software development will be highly valued. This aligns with operations roles that often require understanding technical systems and their impact.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Case Studies of UX Research Projects: Detailed documentation of past research projects, showcasing the research process from problem definition to actionable insights and impact.

• Methodology Application: Examples demonstrating the application of diverse UX research methodologies (e.g., interviews, surveys, usability testing, heuristic evaluations) tailored to specific research questions.

• AI Tool Integration (if applicable): Any projects or research that involved the evaluation or implementation of new tools or technologies to enhance research processes.

• Data Synthesis & Reporting: Clear examples of how raw data was synthesized into meaningful insights and communicated effectively through reports, presentations, or other deliverables.

Process Documentation:

• Research Workflow Design: Evidence of designing or improving research workflows, including steps for participant recruitment, data collection, analysis, and reporting.

• Tool Evaluation Frameworks: Documentation of frameworks or criteria used to evaluate the effectiveness and suitability of research tools or platforms.

• Impact Measurement: Examples of how research findings were translated into measurable improvements or strategic recommendations for product or service development.

📝 Enhancement Note: For an intern role, a formal "portfolio" might be less expected than strong academic work and project examples within their PhD. The emphasis should be on showcasing research process, analytical thinking, and the ability to articulate findings. For this role, highlighting projects involving new methodologies or tool evaluations would be particularly relevant.

💵 Compensation & Benefits

Salary Range: $45.00 per hour.

Benefits:

• Career Development: Opportunities for professional growth and skill enhancement within a leading research organization.

• Flexible Workplace Policy: Support for a hybrid work model, allowing for a balance between on-site collaboration and remote work flexibility.

• Collaborative Culture: Exposure to a strong team environment with opportunities to learn from experienced researchers and industry experts.

• Networking Opportunities: Access to industry professionals and potential for academic publications, enhancing professional visibility.

• Exposure to Cutting-Edge Technology: Hands-on experience with emerging AI tools and their application in real-world research scenarios.

Working Hours: Standard full-time intern hours, estimated at 40 hours per week, with flexibility offered through the hybrid work arrangement.

📝 Enhancement Note: The stated hourly rate is specific. The benefits are framed around professional development and work-life balance, which are key considerations for interns and often reflect the company's operational approach to talent management.

🎯 Team & Company Context

🏢 Company Culture

Industry: Market Research & Advisory Services. Ipsos is a global leader in providing data-driven insights to help organizations understand markets, brands, and behaviors.

Company Size: Large Enterprise (over 10,000 employees globally). This scale offers diverse projects and exposure to various research disciplines.

Founded: 1975. With decades of experience, Ipsos has a deep-seated understanding of research methodologies and client needs.

Team Structure:

• The UX research team at Ipsos is likely integrated within broader research divisions, potentially collaborating with data scientists, strategists, and client account managers.

• Reporting structure will involve a direct manager (likely a Senior UX Researcher or Research Director) and potentially mentors within the internship program.

Methodology:

• Data-Driven Insights: A core principle is the rigorous collection and analysis of data to generate actionable insights.

• User-Centric Approach: Emphasis on understanding user needs, behaviors, and experiences to inform client strategies.

• Innovation in Research: Continuous exploration and development of new research methods and technologies, including AI, to stay at the forefront of the industry.

• Global Collaboration: Leveraging a worldwide network of experts to bring diverse perspectives and expertise to client challenges.

Company Website: https://www.ipsos.com/en-us

📝 Enhancement Note: Ipsos' positioning as a "research company primarily managed by researchers" and its emphasis on "data-driven solutions" and "rigorous understanding of CX and EX" indicate a culture that values analytical rigor, methodological excellence, and a deep commitment to understanding human behavior. For operations professionals, this means a focus on process, data integrity, and the effective application of research outputs.

📈 Career & Growth Analysis

Operations Career Level: This is an internship role designed for a PhD student, typically at an early-to-mid stage of their academic journey. It represents an opportunity to gain specialized, applied research experience within a corporate setting.

Reporting Structure: The intern will report to a designated manager or mentor within the UX Research department. This provides direct guidance and oversight, crucial for learning and development.

Operations Impact: While this is an internship, the work is expected to have a tangible impact by evaluating new tools and methodologies that could shape future research operations at Ipsos. The intern's findings can inform strategic decisions regarding technology adoption and process improvement within the research division.

Growth Opportunities:

• Skill Specialization: Deepen expertise in AI-driven UX research, methodology development, and academic-industry collaboration.

• Industry Exposure: Gain practical experience in a leading global market research firm, understanding client needs and research application.

• Networking: Build connections with industry professionals and researchers, opening doors for future career opportunities.

• Publication Potential: Opportunity to co-author publications or present research findings, enhancing academic and professional profiles.

• Future Employment: Successful interns may be considered for future full-time roles within Ipsos or its network.

📝 Enhancement Note: This internship is positioned as a high-potential learning experience, bridging academic research with industry application. The growth opportunities are clearly defined, focusing on specialized skill development and professional networking, which are critical for advancing within the operations and research fields.

🌐 Work Environment

Office Type: Hybrid work environment. This implies a mix of in-office collaboration and remote work, offering flexibility.

Office Location(s): New York, NY. This major metropolitan hub provides access to diverse talent, clients, and industry events.

Workspace Context:

• Collaborative Spaces: The office environment likely includes collaborative zones designed for team meetings, brainstorming sessions, and cross-functional discussions.

• Technology-Rich: Access to standard office technology, research software, and potentially specialized AI tools relevant to the internship.

• Professional Atmosphere: A corporate setting that balances a focus on rigorous research with a professional and inclusive work culture.

• Hybrid Integration: The workspace is set up to accommodate team members who are both in-office and remote, promoting inclusive communication and collaboration.

Work Schedule: The role is structured around a typical intern schedule of 10-12 weeks, with an estimated 40 hours per week. The hybrid policy allows for flexibility in daily scheduling, balancing work tasks with personal commitments.

📝 Enhancement Note: The hybrid nature of the work environment is a key operational consideration. It requires effective remote collaboration tools and communication strategies, ensuring that interns can contribute effectively regardless of their physical location on any given day.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: Review of academic background, publication record, and relevant research experience.

• Technical/Research Interview: In-depth discussion of research methodologies, AI tool evaluation experience, and ability to handle complex technical topics. This may involve discussing past PhD research or projects.

• Case Study/Project Presentation: Potential for the candidate to present a relevant research project from their PhD or previous work, demonstrating their analytical skills, process, and findings.

• Behavioral/Fit Interview: Assessment of cultural fit, collaboration style, independent work capabilities, and alignment with Ipsos' values.

• Hiring Manager/Team Interview: Final discussion with the hiring manager and potential team members to assess overall fit and answer candidate questions.

Portfolio Review Tips:

• Highlight AI/Tool Evaluation: If you have any projects involving the evaluation or use of new technologies, software, or research tools, emphasize these.

• Showcase Research Process: Clearly articulate the steps taken in your research projects – problem definition, methodology selection, data collection, analysis, and synthesis.

• Quantify Impact: Where possible, demonstrate the impact of your research, whether through academic citations, contributions to product improvements, or actionable insights generated.

• Focus on First Authorship: Emphasize your first-author publications in top-tier conferences as direct evidence of your research capabilities.

• Tailor to the Role: Frame your experience in the context of evaluating AI-powered tools and their impact on research workflows.

Challenge Preparation:

• Anticipate AI Research Questions: Be prepared to discuss the current state of AI in UX research, potential benefits, risks, and ethical considerations.

• Methodology Defense: Be ready to explain why you chose specific research methods for your past projects and how they were effective.

• Technical Communication: Practice explaining complex technical concepts clearly and concisely, as you'll need to do this with both technical and non-technical audiences.

• Problem-Solving Scenarios: Consider how you would approach evaluating a new AI research tool from scratch, including defining criteria and designing a study.

📝 Enhancement Note: The interview process is designed to assess both academic rigor and practical application. A strong emphasis on "academic publication experience" and the ability to discuss "complex computing topics" indicates the need for candidates to be articulate and well-prepared to defend their research and technical understanding.

🛠 Tools & Technology Stack

Primary Tools:

• UX Research Software: Familiarity with common UX research platforms (e.g., UserTesting.com, Qualtrics, SurveyMonkey for surveys/interviews).

• Data Analysis Tools: Proficiency in statistical software (e.g., SPSS, R, Python libraries like Pandas/NumPy) for quantitative analysis.

• Qualitative Analysis Tools: Experience with software for coding and analyzing qualitative data (e.g., NVivo, Dovetail).

• Prototyping/Design Tools (Beneficial): Familiarity with tools like Figma, Sketch, or Adobe XD, to understand the output of UX design.

Analytics & Reporting:

• Data Visualization Tools: Experience with tools like Tableau, Power BI, or Python libraries (Matplotlib, Seaborn) for creating clear visual representations of data.

• Spreadsheet Software: Advanced proficiency in Excel or Google Sheets for data manipulation and basic analysis.

CRM & Automation (Less Direct, but Contextually Relevant):

• While not directly used for research, understanding how CRM systems (e.g., Salesforce) and automation tools feed data into research insights can be beneficial for understanding business context.

📝 Enhancement Note: The role emphasizes research methodologies and AI tool evaluation. While specific proprietary Ipsos tools may not be listed, candidates should highlight their proficiency with a broad range of research, data analysis, and reporting technologies. The mention of "programming and developing computational tools" suggests that experience with scripting languages like Python or R is highly valued.

👥 Team Culture & Values

Operations Values:

• Intellectual Curiosity: A drive to explore new ideas, technologies (like AI), and research frontiers.

• Rigorous Methodology: Commitment to sound research design, data integrity, and objective analysis.

• Impact-Oriented: Focus on generating insights that lead to tangible improvements for clients and users.

• Collaboration: Valuing teamwork, knowledge sharing, and diverse perspectives to solve complex problems.

• Ethical Conduct: Upholding high ethical standards in research practices, data privacy, and reporting.

Collaboration Style:

• Cross-Functional Integration: Working effectively with researchers from different specializations and with client-facing teams.

• Knowledge Sharing: Encouraging open communication and the exchange of ideas and best practices within the team and broader organization.

• Feedback-Driven: Openness to constructive feedback on research designs, findings, and presentations, fostering continuous improvement.

• Proactive Engagement: Taking initiative to contribute ideas and solutions, rather than passively receiving tasks.

📝 Enhancement Note: Ipsos' culture appears to be a blend of academic rigor and applied business impact. The values emphasize a commitment to data-driven insights, ethical practices, and continuous learning, which are crucial for effective operations professionals in any field.

⚡ Challenges & Growth Opportunities

Challenges:

• Rapidly Evolving AI Landscape: Keeping pace with the fast-paced development and integration of AI tools in research requires continuous learning and adaptation.

• Ethical Considerations of AI: Navigating the ethical implications of using AI in user research, such as data privacy, bias, and algorithmic transparency.

• Bridging Academic and Industry: Translating theoretical knowledge and academic research findings into practical, actionable insights for industry clients.

• Evaluating Novel Tools: Developing robust methods to evaluate the effectiveness and reliability of new, unproven AI research technologies.

Learning & Development Opportunities:

• AI in Research Specialization: Gaining hands-on experience with cutting-edge AI tools and developing expertise in their application for UX research.

• Industry Best Practices: Learning how research is conducted at a global scale and understanding client business challenges.

• Methodology Innovation: Contributing to the development and refinement of novel research approaches that integrate AI.

• Professional Networking: Building relationships with leading researchers and industry professionals within Ipsos.

• Publication and Presentation Skills: Honing skills in communicating complex research findings to diverse audiences.

📝 Enhancement Note: The opportunity to work with AI is a significant draw, but it also presents the challenge of staying current and addressing ethical concerns. This aligns with the dynamic nature of operations roles, which often require adapting to new technologies and methodologies.

💡 Interview Preparation

Strategy Questions:

• "Describe a complex research problem you've tackled during your PhD. What was your approach, what challenges did you face, and what were the key outcomes?" (Focus on methodology, problem-solving, and impact).

• "How would you go about evaluating a new AI-powered tool designed to automate user interview transcription and analysis? What criteria would you use, and what would be your research design?" (Tests AI evaluation skills and research design).

Company & Culture Questions:

• "What interests you specifically about Ipsos and this particular internship focus on AI in UX research?" (Demonstrates research into the company and role alignment).

• "How do you approach collaboration with technical teams or individuals with different expertise?" (Evaluates teamwork and communication skills).

Portfolio Presentation Strategy:

• Focus on Process: Walk through one or two key projects, detailing the research question, methodology, your specific role, challenges, and the insights/outcomes.

• Highlight AI/Tool Relevance: If any projects involved evaluating tools, optimizing workflows, or using computational methods, draw attention to these.

• Articulate Impact: Clearly state the contribution of your research, whether it's a publication, a contribution to a larger project, or a significant insight.

• Be Ready for Deep Dives: Prepare to answer detailed questions about your methodology, data analysis, and conclusions.

📝 Enhancement Note: The interview questions are geared towards assessing advanced research capabilities, technical understanding, and the ability to apply academic knowledge to industry challenges. Candidates should be prepared to discuss their PhD work in detail and articulate how it relates to the internship's focus on AI and research operations.

📌 Application Steps

To apply for this PhD UX Research Intern position:

• Submit your application through the provided link on the Ipsos Careers portal.

• Tailor Your Resume/CV: Highlight your PhD research, first-author publications, and any experience with UX research, AI tools, or technical analysis. Quantify achievements where possible.

• Prepare Your Portfolio/Research Examples: Have clear examples of your research projects ready to discuss, focusing on methodology, challenges, and outcomes. Be prepared to articulate your process for evaluating tools or developing new methods.

• Research Ipsos: Understand Ipsos' mission, industry position, and commitment to innovation. Familiarize yourself with their UX/research offerings and tailor your interest to their specific work.

• Practice Interview Responses: Prepare answers for common behavioral, technical, and situational questions, especially those related to AI, research methodology, and independent work.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions. The application deadline is February 27, 2026.