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Post Doctoral Medical Fellow - Digital Health, Clinical Development, Clinical Research

Job in Ridgefield, Fairfield County, Connecticut, 06877, USA
Listing for: Boehringer Ingelheim GmbH
Full Time position
Listed on 2026-03-15
Job specializations:
  • IT/Tech
    Data Scientist, Data Analyst
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below

Description

The gBDS /Med Data/AI -- Boehringer Ingelheim is seeking a postdoctoral research fellow to help leverage scientifically rigorous digital health technologies that accelerate clinical development across therapeutic areas.

The fellow will drive innovation in digital endpoints, remote monitoring technologies, and multimodal data analytics to enhance multiple facets of clinical trials—from identifying and recruiting suitable patients to capturing meaningful real-world outcomes such as quality of life, functional capacity, and disease progression. This research-focused role emphasizes translating digital health innovations into, deployable solutions that improve trial outcomes by better understanding patients’ journeys in the real-world setting.

Work will be anchored in Boehringer Ingelheim’s core therapeutic areas — e.g. respiratory, cardiovascular-renal-metabolic, oncology, CNS — with digital measures selected/evaluated in the context of clinically meaningful endpoints for those disease areas.

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the companies´ success. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, mobility, networking and work-life balance.

Our competitive compensation and benefit programs reflect Boehringer Ingelheim´s high regard for our employees.

Duties & Responsibilities
  • Under supervisor/s guidance, lead research focused on evaluating, testing, and deploying digital health technologies (wearables, sensors, smartphone apps, patient-reported outcomes) to accelerate clinical development as well as manuscript preparation and submissions
  • Conduct statistical analysis of multimodal real-world behavioral data to assess associations with key clinical outcomes of interest (e.g., treatment response, disease progression, adherence, data quality, patient phenotypes/stratification, digital endpoint validation, quality of life)
  • Proactively design and lead the development of reusable, reproducible data analysis pipelines for extracting quality metrics, features, and validated digital endpoints from multimodal clinical trial data
  • Design and execute validation studies to establish the scientific rigor, reliability, and clinical meaningfulness of digital health measures for trial use (e.g., patient identification/screening, enrollment optimization, quality-of-life assessment, functional outcomes)
  • Collaborate with interdisciplinary and cross-functional teams (clinical development, biostatistics, data science, clinical operations, regulatory affairs) to communicate and present research findings through presentations and scientific reports
Requirements
  • Ph.D. from an accredited institution earned before the start date at Boehringer Ingelheim. Preferred degree in a quantitative field such as biomedical engineering, statistics, computer science, electrical engineering, data science, or a related discipline
  • Demonstrable proficiency in at least one scripting language (Python or R preferred) and experience writing reusable, version-controlled (Git), and well-documented code
  • Demonstrated scientific experience in digital health research as evidenced by publications, presentations, or successful digital health project implementations
  • Strong background in applied data science, signal processing, time-series analysis, and machine learning/statistics, preferably in healthcare or clinical research domains
  • Experience analyzing temporal health-related data from digital health applications, wearable/smartphone sensors (e.g., accelerometer, activity, sleep, voice or other physiological/behavioral measures) is strongly preferred
  • Familiarity with clinical outcome assessment (COA) frameworks and patient-centered measurement, including PRO, ClinRO, ObsRO, and PerfO categories; experience with ePRO/eCOA instruments or FDA PRO…
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