
Breakthroughs that change patients' lives.
Postdoctoral Fellow, AI for Quantitative Medicine
Use Your Power for Purpose
At Pfizer, our purpose is to deliver breakthroughs that transform patients' lives. Central to this mission is our Research and Development team, which strives to convert advanced science and cutting-edge technologies into impactful therapies and vaccines. Whether you are engaged in discovery sciences, ensuring drug safety and efficacy, or supporting clinical trials, your role is crucial. You will leverage innovative design and process development capabilities to expedite the delivery of top-tier medicines to patients globally.
This Postdoctoral Fellow will lead innovative research at the intersection of artificial intelligence, medical imaging, pharmacometrics, and oncology drug development, with the goal of transforming how early treatment response is measured and used in clinical decision-making. This role will focus on developing and validating AI-powered quantitative imaging biomarkers that provide earlier, more sensitive, and more prognostic measures of treatment efficacy than current standards.
Working within a global R&D environment, the Fellow will leverage large-scale multimodal clinical trial datasets—integrating radiological imaging, pharmacokinetics/pharmacodynamics (PK/PD), and clinical outcomes—to advance next-generation early response endpoints. The work will potentially support early oncology drug development, dose selection, and trial design and materially accelerate portfolio decisions and improve probability of clinical success.
The role offers a unique opportunity to conduct impact-driven research with real-world translational application, collaborating closely with cross-functional partners across Oncology Development, Data Sciences & Analytics, and R&D AI innovation teams, as well as external AI and academic collaborators.
What You Will Achieve
In this role, you will:
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Scientific Leadership in AI-Enabled Biomarker Development Provide intellectual leadership in the development and validation of advanced AI models (e.g., deep learning–based imaging biomarkers) to quantify and predict tumor response from longitudinal clinical trial data.
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Integration of Multimodal Clinical Data Lead the integration of medical imaging, PK/PD, and clinical outcome data to establish mechanistic and predictive relationships between early response dynamics and downstream survival outcomes.
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Developing Novel Quantitative Modeling Approaches Explore development of modeling approaches (empirical, semi-mechanistic) that integrate AI enabled tumor response data to long term clinical outcomes
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Innovation in Early Response Endpoints Drive the conceptualization and evaluation of novel, continuous early response endpoints that address limitations of conventional criteria (e.g., RECIST), with a focus on clinical relevance and robustness.
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Translational Impact on Drug Development Decisions Translate methodological advances into scalable frameworks that can inform dose optimization, trial design, and early efficacy decision-making across oncology programs
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Cross-Functional and External Collaboration Collaborate effectively with internal stakeholders across Oncology Early- and Late-Stage Development, Data Sciences & Analytics, and AI innovation partners, as well as external technology and academic collaborators.
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Scientific Rigor and Reproducibility Ensure high standards of scientific rigor, validation, and documentation to support internal adoption, regulatory interactions, and broader reuse of developed methods and workflows.
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Knowledge Dissemination and Thought Leadership Communicate results through internal presentations, external scientific publications, and conference contributions, contributing to the organization’s reputation as a leader in AI-enabled R&D.
Here Is What You Need (Minimum Requirements):
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PhD (or equivalent doctoral degree) completed by start date in a relevant field such as Biomedical Engineering, Chemical Engineering, Computational Biology, Biostatistics, Mathematics, Physics, Computer Sciences, Pharmaceutical Sciences or a related quantitative discipline.
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Demonstrated research experience applying machine learning or deep learning methods to biomedical, imaging, PK/PD, or clinical data.
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Proficient in at least one programing language (e.g., Python, R, MATLAB, etc.).
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Experience in machine learning/deep learning (Py Torch, Tensor Flow), medical image analysis, and/or pharmacometrics.
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Strong foundation in deep learning methodologies (e.g., CNNs, Transformers, vision-language or multimodal models).
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Experience in machine learning/deep learning (Py Torch, Tensor Flow), medical image analysis, and/or pharmacometrics
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Experience working with large, complex datasets and performing model development, validation, and performance evaluation.
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Ability to translate methodological innovation into practical, data-driven insights within a regulated or applied research environment.
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Strong written and verbal communication skills, with the ability to clearly explain complex technical concepts to interdisciplinary audiences.
Bonus Points If You Have:
(Preferred Requirements):
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Prior experience inoncology, medical imaging, or clinical trial PK/PD data analysis.
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Familiarity with tumor response assessment frameworks (e.g., RECIST) and their limitations in oncology.
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Experience integrating imaging data with clinical outcomes, PK/PD, or survival analysis.
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Track record of publications in high-impact journals or presentations at major scientific conferences.
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Experience collaborating with industry, translational research teams, or external technology partners.
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Interest in advancing AI methods with direct impact on drug development strategy and clinical decision-making.
Additional Information
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Relocation support available
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Work Location Assignment: Hybrid
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.
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
Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, disability or veteran status. Pfizer also complies with all applicable national, state and local laws governing nondiscrimination in employment as well as work authorization and employment eligibility verification requirements of the Immigration and Nationality Act and IRCA. Pfizer is an E-Verify employer. This position requires permanent work authorization in the United States.
Pfizer endeavors to make www.pfizer.com/careers accessible to all users. If you would like to contact us regarding the accessibility of our website or need assistance completing the application process and/or interviewing, please email disabilityrecruitment@pfizer.com. This is to be used solely for accommodation requests with respect to the accessibility of our website, online application process and/or interviewing. Requests for any other reason will not be returned.
Research and Development:
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Pfizerについて

Pfizer
PublicPfizer Inc. is an American multinational pharmaceutical and biotechnology corporation headquartered at The Spiral in Manhattan, New York City. Founded in 1849 in New York by German entrepreneurs Charles Pfizer (1824–1906) and Charles F.
10,001+
従業員数
New York City
本社所在地
$280B
企業価値
レビュー
10件のレビュー
4.0
10件のレビュー
ワークライフバランス
3.2
報酬
4.3
企業文化
4.1
キャリア
3.4
経営陣
3.5
72%
知人への推奨率
良い点
Good salary and competitive compensation
Supportive management and team collaboration
Innovative and interesting projects
改善点
High workload and overwhelming demands
Long hours and fast-paced environment
Limited career advancement opportunities
給与レンジ
11件のデータ
Junior/L3
Mid/L4
Senior/L5
L3
Junior/L3 · SENIOR ASSOCIATE SCIENTIST
1件のレポート
$86,450
年収総額
基本給
$66,500
ストック
-
ボーナス
-
$86,450
$86,450
面接レビュー
レビュー4件
難易度
3.0
/ 5
期間
14-28週間
面接プロセス
1
Application Review
2
HR Screen
3
HireVue Video Interview
4
Hiring Manager Interview
5
Final Interview/Panel
6
Offer Decision
よくある質問
Behavioral/STAR
Past Experience
Culture Fit
Technical Knowledge
Case Study
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