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2027 Future Talent Program - Data, AI, and Genome Sciences - Intern

USA - Massachusetts - Cambridge (320 Bent Street)

Pay
$39,908–111,111/yearAnnual period assumed — pay source
Salary range: The salary range for this role is $39,908 - $111,111 FTP2027
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Work setting
Hybrid — work setting source
Flexible Work Arrangements: Hybrid Shift:
Read the full posting
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
VISA Sponsorship:
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Apply at Merck

What you’ll work on

Full posting
  • Develop statistical and computational methods and pipelines for Perturb-seq datasets

  • Develop approaches to assess and validate in silico perturbation predictions from single-cell foundation models

From the employer’s posting
Develop statistical and computational methods/pipelines to utilize, analyze, interpret, and validate perturb-seq datasets.
Develop approaches to assess, interpret, and validate in silico perturbation predictions from single-cell foundation models.

What you’ll bring

All qualifications

Preferred experience

  • 11/27/2026*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date.
Qualification wording
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.
Education & alternatives
Required Education and Skills: - Must be currently enrolled in a PhD degree in Computer Science, Statistics, Bioinformatics, Computational Biology, or related technical field. - Must be available to work full-time for 10-12 weeks beginning in May or June of 2027.

Tools in this posting

  • Python
  • PyTorch
Source — Tool mentions in context
- Demonstrated experience with single-cell omics data (e.g., scRNA-seq, perturb-seq). - Excellent software design and development skills and strong proficiency in Python. - Excellent communication skills and ability to work collaboratively in a multi-disciplinary team.
- Experience with advanced statistics and/or Bayesian methods. - Proficiency in modern ML frameworks (e.g., PyTorch) and experience implementing scalable solutions for complex tasks. - Publications in journals or conferences.

Posting record

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Actively hiringFirst seen by us 5 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 23, 2026 · 5 days ago
Recorded sightings
22
Last seen by us
Oct 29, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

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Job description

View original posting ↗

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 1 open position on the AI/ML Data Science, In Silico Perturbation Team. Candidates can apply for the opportunity to be involved in one or more of the projects listed below. The projects are 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 students with computational skillsets.


Location: Cambridge, MA

Term: Full-time, 10-12 weeks


AI/ML Data Science:

  • Develop statistical and computational methods/pipelines to utilize, analyze, interpret, and validate perturb-seq datasets.
  • Develop approaches to assess, interpret, and validate in silico perturbation predictions from single-cell foundation models.

Required Education and Skills:

  • Must be currently enrolled in a PhD degree in Computer Science, Statistics, Bioinformatics, Computational Biology, or related technical field.
  • Must be available to work full-time for 10-12 weeks beginning in May or June of 2027.
  • Demonstrated experience with single-cell omics data (e.g., scRNA-seq, perturb-seq).
  • Excellent software design and development skills and strong proficiency in Python.
  • Excellent communication skills and ability to work collaboratively in a multi-disciplinary team.

Preferred Skills and Experience:

  • Motivated to impact biological projects with independent project leadership experience.
  • Experience with biological foundation models (e.g., single-cell foundation models).
  • Experience with advanced statistics and/or Bayesian methods.
  • Proficiency in modern ML frameworks (e.g., PyTorch) and experience implementing scalable solutions for complex tasks.
  • Publications in journals or conferences.

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:

Current Employees apply HERE

Current Contingent Workers apply HERE

US and Puerto Rico Residents Only:

Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities. Please click here if you need an accommodation during the application or hiring process.

As an Equal Employment Opportunity Employer, we provide equal opportunities to all employees and applicants for employment and prohibit discrimination on the basis of race, color, age, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, or other applicable legally protected characteristics.  As a federal contractor, we comply with all affirmative action requirements for protected veterans and individuals with disabilities.  For more information about personal rights under the U.S. Equal Opportunity Employment laws, visit:

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EEOC GINA Supplement​

We are proud to be a company that embraces the value of bringing together, talented, and committed people with diverse experiences, perspectives, skills and backgrounds. The fastest way to breakthrough innovation is when people with diverse ideas, broad experiences, backgrounds, and skills come together in an inclusive environment. We encourage our colleagues to respectfully challenge one another’s thinking and approach problems collectively.

Learn more about your rights, including under California, Colorado and other US State Acts

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

Los Angeles Residents Only: We will consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles’ Fair Chance Initiative for Hiring Ordinance

Search Firm Representatives Please Read Carefully 
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:

1st - Day

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.

Source details

View original posting ↗

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Pay
Salary range: The salary range for this role is $39,908 - $111,111 FTP2027
Location & working pattern

USA - Massachusetts - Cambridge (320 Bent Street)

Flexible Work Arrangements: Hybrid Shift:
Work authorization
No relocation VISA Sponsorship: No

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