Bioinformatician I

Duke Careers•Durham, NC

1d•$82,159 - $132,722

About The Position

As the Bioinformatician I, you'll play a key role in advancing innovative translational medicine research by helping build and maintain the sophisticated data infrastructure that powers cutting-edge clinical and scientific discovery. Working alongside interdisciplinary teams of researchers, clinicians, engineers, and data scientists, you'll contribute to multi-modal data fusion initiatives that integrate electronic health records, physiological waveform data, and multi-omic datasets. Your expertise will help transform complex healthcare data into meaningful resources that drive impactful research and improve patient outcomes. Join a nationally recognized Department of Surgery and take on some of the most complex data challenges in healthcare research. In this role, you'll help architect scalable systems and high-throughput pipelines that support advanced machine learning, reinforcement learning, and foundation model research across large-scale clinical environments.

Requirements

Strong programming expertise in Python and advanced SQL, including large-scale query optimization.
Experience designing, developing, and maintaining robust data pipelines in cloud computing environments.
Knowledge of distributed data processing frameworks and large-scale data engineering principles.
Experience working with electronic health records and complex healthcare datasets.
Familiarity with containerization technologies such as Docker and deployment of scalable applications.
Strong communication skills with the ability to collaborate effectively with both technical and non-technical stakeholders.

Nice To Haves

Experience with OMOP Common Data Model or other healthcare interoperability standards.
Experience processing high-frequency physiological waveform data.
Familiarity with Azure, AWS, or Google Cloud Platform environments.
Knowledge of machine learning infrastructure, reinforcement learning, or foundation model research environments.
Experience working with large-scale clinical research initiatives or multi-center collaborations.

Responsibilities

Design, build, and optimize distributed data processing workflows utilizing technologies such as PySpark, Dask, and cloud-based computing platforms.
Develop and maintain automated, version-controlled ETL/ELT pipelines that support large-scale clinical and research datasets.
Process and manage terabyte-scale inpatient healthcare data, including electronic health records, physiological waveform data, and multi-omic datasets.
Support multi-site initiatives and federally sponsored programs through rigorous data validation, verification, and quality assurance activities.
Contribute to research efforts focused on reinforcement learning methodologies and multi-modal time-series foundation models.
Standardize and harmonize complex healthcare data using clinical interoperability frameworks such as the Observational Medical Outcomes Partnership (OMOP) Common Data Model.
Collaborate with technical and clinical teams to translate complex data requirements into practical research solutions.
Implement scalable cloud-based data management solutions within Azure, AWS, or comparable environments.
Utilize optimized data storage formats, including Parquet and HDF5, to support efficient retrieval and analysis of large datasets.
Partner with multidisciplinary stakeholders to advance innovative research initiatives across multiple institutions and research networks.