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Research and Development (R&D) at Procter & Gamble, the largest consumer packaged goods company in the world, includes a diverse group of roles that contribute to the innovation and development of our products. It encompasses roles in product research, formulation, testing, and scientific analysis. You will find variety and excitement starting Day 1.

This internship is specifically designed for individuals working towards a PhD who are developing proficiency in their field. As an intern or co-op in management, you will have the opportunity to learn from experienced professionals in a supportive environment.  This is a 12-week paid internship, designed to provide you with a solid foundation for future career growth. The internship will take place from May (potentially early June) to August of 2027.  Join us at P&G, where your contributions will play a vital role in shaping the future of consumer products!
 

The Opportunity:

P&G has an opportunity for a PhD intern to work in our Feminine Care business working in the space of Data Scientist & Gen AI.  This role leverages current Gen AI technology, multi-discipline knowledge and R&D product innovation cycle, especially by leveraging data and digital approaches. The candidate will create Gen AI tool as co-pilot to guide and influence technical project direction and enable fast problem solving by leveraging collective knowledge in our data & modeling eco-system. The candidate should demonstrate strong scientific/engineering skills through advance model development and application development. 

You will investigate how active learning and sequential experimentation can accelerate learning in R&D. Using historical consumer study and simulation datasets, the project will evaluate whether uncertainty estimates can identify the most informative next study, measurement, or simulation to perform. Rather than exploring the design space uniformly, the goal is to prioritize experiments that are expected to provide the greatest reduction in uncertainty and the highest learning value. This work will treat consumer studies and first-principles simulations as two applications of the same underlying problem: how to allocate experimentation resources more efficiently.  
 

The Ideal Candidate:

• Experience with entrepreneurial/startups and/or industrial experience are strongly preferred. 
• Has strong ownership & self-leadership skills to understand the business objective and technical problem to be solved.
• Has experience collaborating with multi-functional teams.
• Has the ability to recognize opportunities for capabilities or technologies that can be reapplied across programs.
• Can independently work project priorities, multi-task, and handle a wide variety of complex, non-routine/routine tasks in a fast-paced environment. 

Key Responsibilities:

• Using historical consumer study and simulation datasets to evaluate uncertainty
• Identify next study, simulation, and measurement based on reduction of uncertainty
• Optimize experimental resources
• Create a prototype work process to demonstrate success

Job Qualifications

Required Qualifications:

• Education: Working towards a PhD in Computer Science, Machine Learning, Statistics, Mechanical Engineering, Computational Physics, Computational Engineering, Applied Mathematics, or Data Science.  
• Active learning / sequential experimental design — central to recommending the next most informative consumer study or simulation. 
• Probabilistic machine learning / Bayesian statistics — needed to represent prediction uncertainty and update confidence as evidence arrives. 
• Surrogate modeling — needed for both consumer-response prediction and simulation-response approximation. 
• Python — required for model development, simulation, and analysis; PyTorch, scikit-learn, BoTorch, GPyTorch, or similar tools would be useful. 
• Experimental design and model evaluation — needed to compare active learning policies against baselines and define success metrics. 
• Available to work a 12-week internship from May/early June to August in the summer of 2027, and at least 3 days/week onsite at Winton Hill Business Center.
   

Preferred Qualifications/Experience:

• Bayesian optimization 
• Multi-armed bandits or reinforcement learning 
• Uncertainty quantification 
• Gaussian processes, evidential models, Bayesian neural networks, or ensembles 
• Scientific computing 
• CFD / FEA familiarity, if using first-principles simulation examples 
• Generative AI / AI-agent prototyping, but only as a communication layer, not the core research contribution 
   

Just so you know:

At P&G, we believe that diverse experiences help build strong leaders. Mobility is a key component of many management careers, providing opportunities to grow through different assignments, locations, and business challenges. Candidates should be prepared to consider relocation opportunities throughout their career as business needs and development opportunities arise. 

Compensation for roles at P&G varies depending on a wide array of non-discriminatory factors including but not limited to the specific office location, role, degree/credentials, relevant skill set, and level of relevant experience. At P&G compensation decisions are dependent on the facts and circumstances of each case. Total rewards at P&G include salary + bonus (if applicable) + benefits.  Your recruiter may be able to share more about our total rewards offerings and the specific salary range for the relevant location(s) during the hiring process.

We are committed to providing equal opportunities in employment. We value diversity and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Immigration Sponsorship is not available for this role. For more information regarding who is eligible for hire at P&G along with other work authorization FAQ’s, please click HERE.

Procter & Gamble participates in E-Verify.

Qualified individuals will not be disadvantaged based on being unemployed.

P&G is dedicated to meeting the needs of applicants requesting an accommodation/adjustment due to a disability in order to complete the online application process.  If you have a disability that affects your ability to complete our online application process, please visit our Disability Accommodation Page.

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