Skip to Content

Jobs

Please note:

We strongly encourage applications from individuals with disabilities, including those with autism or other forms of neurodivergence. Our company is committed to diversity, inclusivity, and creating a supportive work environment for all employees.

Postdoctoral Scientist – AI & Machine Learning for Predictive Drug Absorption

|  Posted On: Jun 15, 2026

location:Cambridge, MA 02139

Duration:Direct Hire (Full Time)

mode of work:On-site

Log In and Apply

Job Summary

Job Title:  
Postdoctoral Scientist – AI & Machine Learning for Predictive Drug Absorption
Posted Date:  
Jun 15, 2026
Duration:  
Direct Hire (Full Time)
Shift(s):  

09:00 - 18:00

Salary ($): 
64600.00 - 107600.00 per Yearly (compensation based on experience and qualifications)
We care about you! Explore Rangam’s benefits information

Description

Rangam is seeking candidates for a Direct Hire role as a Postdoctoral Scientist – AI & Machine Learning for Predictive Drug Absorption Iwith our client Pfizer, one of the world’s largest pharmaceutical companies. Seeking candidates in Cambridge, MA  ,Groton Connecticut willing to relocate.

Shape the Future of Oral Drug Development with AI-Driven Predictive Science

Last day to apply: June 30th

Pfizer Research & Development is seeking a highly motivated Postdoctoral Scientist with deep expertise in Artificial Intelligence (AI) and Machine Learning (ML) to advance the prediction of oral drug absorption and formulation performance. In this role, you will play a critical part in developing next-generation predictive models that help transform how drug products are designed, optimized, and translated into clinical success.

 

You will focus on building, evaluating, and interpreting advanced machine learning models using large, diverse datasets drawn from multiple scientific and clinical sources. Your work will emphasize scalability, interpretability, and real-world applicability ensuring that model outputs are not only technically robust but also scientifically meaningful and decision relevant. A key aspect of this role is the development of explainable modeling approaches, including physics-informed and mechanism-informed learning, to bridge data-driven insights with fundamental pharmaceutical science.

 

Through this work, you will directly contribute to enabling earlier, faster, and more confident decision-making across Pfizer’s R&D portfolio. Your models will help inform formulation strategies, predict in vivo performance, and reduce uncertainty in the development process, ultimately accelerating the delivery of high-quality medicines to patients.

This position is embedded within the Drug Product Design and Supply (DPDS) organization, part of Pfizer’s broader Pharmaceutical Sciences division. The role is based in Groton, Connecticut, or Cambridge, Massachusetts, and offers a highly collaborative environment where you will partner closely with interdisciplinary experts across Digital & AI, Clinical Pharmacology, Pharmacometrics, and other quantitative R&D teams. Together, you will integrate cutting-edge AI methodologies with deep domain expertise to solve complex challenges at the intersection of data science and drug development.

Key Responsibilities

 

  • Design, train, and evaluate machine-learning models for predicting oral drug absorption–related outcomes from high-dimensional datasets.
  • Develop end-to-end ML pipelines, including data ingestion, feature engineering, model training, validation, and performance benchmarking.
  • Work with large, diverse datasets, including experimental biopharmaceutics data and clinical pharmacokinetic datasets, and internally generated datasets relevant to predictive modelling.
  • Apply and compare a range of ML approaches, including tree-based methods, neural networks, surrogate models, probabilistic approaches for uncertainty-aware prediction.
  • Focus on model interpretability and explainability, linking learned patterns to scientifically meaningful drivers where possible.
  • Quantify model robustness, generalizability, and uncertainty, particularly in data-sparse or extrapolative scenarios.
  • Translate ML outputs into actionable insights for drug development teams, rather than purely academic metrics.
  • Communicate results through internal technical reports, cross-functional presentations, and peer-reviewed publications.
  • Contribute to the establishment of AI-enabled predictive platforms within Pfizer R&D.

 

REQUIRED QUALIFICATIONS (must have)

 

  • PhD in Machine Learning, Data Science, Applied Mathematics, Computational Sciences, Engineering, Pharmaceutical Sciences, or a closely related quantitative discipline.
  • Provide two letters of recommendation with your application (e.g. professors/PI). 
  • Willingness to commit to the fixed-term full-time postdoctoral fellowship (duration: 2–4 years).
  • Less than 2 years post-doctoral experience. 
  • At least 1 first-author scientific research article in high-quality specialty or general readership journals. 
  • Strong foundation in machine learning and statistical modelling, with hands-on experience building and evaluating predictive models.
  • Proficiency in Python and/or R for data analysis and ML development (e.g. scikit-learn, PyTorch, TensorFlow, or similar).
  • Experience working with large, heterogeneous datasets and structured scientific data.
  • Demonstrated research productivity, evidenced by peer-reviewed publications or equivalent scientific outputs.
  • Ability to collaborate effectively in multidisciplinary research environments.

 

Preferred Qualifications (nice to have)

 

  • Experience applying ML to scientific, pharmaceutical or biomedical, datasets.
  • Familiarity with model interpretability, explainable AI, or uncertainty quantification.
  • Exposure to mechanistic modelling, including physiologically based pharmacokinetic (PBPK) and physiologically based biopharmaceutics modeling (PBBM), simulation-derived data, or physics-informed / mechanism-informed learning.
  • Interest in translating ML models into real-world decision-support tools, rather than purely predictive benchmarks.
  • Strong scientific presentation skills.

 

Training & Development

 

This position is part of the Pfizer Research & Development Postdoctoral Training Program and offers:

  • Mentorship from senior scientists in quantitative drug development.
  • Exposure to real R&D decision-making at scale.
  • Opportunities for publication, and cross-site collaboration.
  • Structured professional development within a world-class pharmaceutical research environment.


PHYSICAL/MENTAL REQUIREMENTS

Ability to perform complex data analysis

Ability to perform mathematical calculations

 

NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS

 

  • Will be required to occasionally travel (0-5%)
  • Relocation support is available
  • Last day to apply: June 30th


The annual base salary for this position ranges from $64,600.00 to $107,600.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 7.5% of the base salary. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.



This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.




Relocation assistance may be available based on business needs and/or eligibility.




Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

Sunshine Act

Pfizer reports payments and other transfers of value to health care providers as required by federal and state transparency laws and implementing regulations.  These laws and regulations require Pfizer to provide government agencies with information such as a health care provider’s name, address and the type of payments or other value received, generally for public disclosure.  Subject to further legal review and statutory or regulatory clarification, which Pfizer intends to pursue, reimbursement of recruiting expenses for licensed physicians may constitute a reportable transfer of value under the federal transparency law commonly known as the Sunshine Act.  Therefore, if you are a licensed physician who incurs recruiting expenses as a result of interviewing with Pfizer that we pay or reimburse, your name, address and the amount of payments made currently will be reported to the government.  If you have questions regarding this matter, please do not hesitate to contact your Talent Acquisition representative.

 

EEO & Employment Eligibility

It is the policy of Rangam Consultants, Inc. to provide equal employment opportunities to all applicants and employees without regard to any legally protected status such as race, color, religion, gender, national origin, age, disability or veteran status. 

To find out more about Rangam and this role, click the apply button.

 

AI-Assisted Application Screening

As part of our recruitment process, we may use automated tools or AI-enabled technologies to assist with resume screening and candidate matching. These tools help our recruitment team review applications more efficiently, but they do not make hiring decisions. All final decisions are made by human reviewers.