Future Talent Program Intern - AI/ML Biomedical Imaging and Computational Pathology

Job Description

The Future Talent Program within our Research & Development Division Data, AI, and Genome Sciences (DAGS) Department is offering internships that last 10-12 weeks. We have an open position in the AI/ML imaging group. Candidates can apply for the opportunity to be involved in the project described below. The project is designed to enable students to further develop their skills and to evaluate if we are the right company for their long-term goals. We are seeking highly motivated and talented students with computational skillsets.

AI/ML – Biomedical Imaging and Computational Pathology 

Within DAGS, our AI/ML team develops cutting-edge AI methods to accelerate drug target and biomarker discovery. The intern will contribute to our efforts in developing next-generation computational approaches for biomedical imaging and computational pathology.

Specific responsibilities include:

• Develop and apply foundation model-based AI methods to extract biologically meaningful and generalizable representations from histopathology images and spatial omics. 

• Design interpretable computational approaches to characterize model representations using biologically grounded features, such as morphological patterns and tumor microenvironment architecture.

• Integrate image-derived features with patient outcome and molecular data to support biological hypothesis generation and biomarker discovery. 

• Collaborate with a multidisciplinary team spanning data science, computational pathology, biology, and translational research. 

Required Education and Skills:

• Must be currently enrolled in a PhD program in Computer science, AI/ML, Computational biology, Biomedical Engineering, Bioinformatics, Statistics or a related field of study.  

• Must be available to work full-time for 9-12 weeks beginning in May or June of 2027.  

• Proficiency with Python programming and modern deep learning frameworks (e.g., PyTorch) 

• Strong communication and interpersonal skills and must be able to work well in a collaborative team environment. 

Preferred Skills and Experience:

• Familiarity with one or more of the following: computer vision, natural language processing, representation learning, foundation models, interpretable/explainable AI, and generative AI. 

• Experience with biomedical or scientific data types (e.g., medical imaging, genomics, spatial omics, clinical datasets). 

• Track record of scientific communication (publications, conference presentations) 

Please note that this position may be closed before the posted end date or may remain open longer, at the discretion of the company.

Salary range:

The salary range for this role is $39,908 - $111,111

FTP2027

RL2027

Required Skills:

Preferred Skills:

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Current Contingent Workers apply HERE

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San Francisco Residents Only: We will consider qualified applicants with arrest and conviction records for employment in compliance with the San Francisco Fair Chance Ordinance

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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails. 

Employee Status:

Intern/Co-op (Fixed Term)

Relocation:

No relocation

VISA Sponsorship:

No

Travel Requirements:

No Travel Required

Flexible Work Arrangements:

Hybrid

Shift:

Not Indicated

Valid Driving License:

No

Hazardous Material(s):

NA

Job Posting End Date:

11/27/2026

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.