September 30, 2024
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Atlanta Metropolitan Area, United States
September 30, 2024
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Position Summary
The Cardiovascular Research Institute ( CVRI ) at the Morehouse School of Medicine aims to be the leading transformational force for health equity in Digital Epidemiology and research. Over the past decade, the CVRI has successfully recruited a talented critical mass of faculty with a wide breadth of scientific expertise that has enriched the intellectual capital of the institution and created one of the largest research portfolios at MSM . Our ongoing process of strategic planning and evaluation has enabled CVRI to build upon its success and emerge as an internationally recognized Center of Excellence in cardiovascular science. Our approach focuses on faculty, research infrastructure and our future scientists. The dynamic role of the Machine Learning Engineer will wear several hats and have the opportunity to support the development of many academic medical innovation projects within the Cardiovascular Research Institute. This role will be responsible for designing, developing, and validating novel machine learning approaches for early prediction of chronic disease and other clinical conditions. Collaborate with experts in machine learning and distributed systems. Additionally, in this role you will maintain current knowledge of developments in allied health sciences, modeling, and machine learning analysis, in conjunction with the use of technology to identify and evaluate new data science tools and methods to support current and future efforts. You will help develop machine learning models on real-time data and facilitate community-based participatory research, which is central to addressing the social determinants of health that impact disparities and the susceptibility of vulnerable populations to chronic disease.
Minimum Qualifications
Bachelor’s or Masters in a Computer Science, Engineering, Mathematics or related field and a track record of producing high quality research. Minimum of two (2) years of professional experience working with machine learning libraries and real-world data science problems. Experience putting models into production and monitoring their effectiveness. Must have the ability to express complex statistical concepts and technical information to researchers and non-scientific audiences Problem solver with excellent analytical skills. A commitment to fostering and upholding an inclusive work environment.
Preferred Qualifications
Minimum of five (5) years of experience in statistics, statistical methods, and statistical software. Experience leading projects and setting the technical direction. Prior publication of high-quality peer-reviewed research articles. Experience in one or more of the following: Domain knowledge in biomedical informatics, healthcare, or a related field Strong programming skills in Python, experience with machine learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with cloud services ( AWS , GCP , Azure). Experience using statistical software for analyses (e.g., Stata, SAS , R). Familiarity with biostatistics or principles of analyzing public health data. Experience working with and deploying machine learning models Experience providing data management and analytic support for complex surveys, longitudinal cohort studies, and/or randomized controlled trials. Data ingestion pipelines, data analysis, data visualization and the ability to learn other programming languages as needed
Description of Job Duty
Design, development and delivery of machine learning and deep learning solutions, including problem definition, data acquisition, exploration, training, testing, and evaluating machine learning models, and creating end-to-end pipelines and solutions in production. Manage multiple initiatives to create and improve the CVRI’s AI’s models and analytics. Responsible for working across the entire machine learning pipeline, including data exploration, feature engineering, model training, deployment, monitoring, and calibration/retraining. Collaborate closely with research faculty and staff, such as project managers, graphic artists, UX designers, other developers, systems analysts and sales and marketing professionals. Develop automated systems and tools to process, clean, and verify data integrity. Provide analysis and support data interpretation to both technical expert and lay users of public health data that include structured and unstructured data, such as free text, images, and data of mixed types. Assist in monitoring data quality issues as they relate to user data products, and collaborate with Information
The Cardiovascular Research Institute ( CVRI ) at the Morehouse School of Medicine aims to be the leading transformational force for health equity in Digital Epidemiology and research. Over the past decade, the CVRI has successfully recruited a talented critical mass of faculty with a wide breadth of scientific expertise that has enriched the intellectual capital of the institution and created one of the largest research portfolios at MSM . Our ongoing process of strategic planning and evaluation has enabled CVRI to build upon its success and emerge as an internationally recognized Center of Excellence in cardiovascular science. Our approach focuses on faculty, research infrastructure and our future scientists. The dynamic role of the Machine Learning Engineer will wear several hats and have the opportunity to support the development of many academic medical innovation projects within the Cardiovascular Research Institute. This role will be responsible for designing, developing, and validating novel machine learning approaches for early prediction of chronic disease and other clinical conditions. Collaborate with experts in machine learning and distributed systems. Additionally, in this role you will maintain current knowledge of developments in allied health sciences, modeling, and machine learning analysis, in conjunction with the use of technology to identify and evaluate new data science tools and methods to support current and future efforts. You will help develop machine learning models on real-time data and facilitate community-based participatory research, which is central to addressing the social determinants of health that impact disparities and the susceptibility of vulnerable populations to chronic disease.
Minimum Qualifications
Bachelor’s or Masters in a Computer Science, Engineering, Mathematics or related field and a track record of producing high quality research. Minimum of two (2) years of professional experience working with machine learning libraries and real-world data science problems. Experience putting models into production and monitoring their effectiveness. Must have the ability to express complex statistical concepts and technical information to researchers and non-scientific audiences Problem solver with excellent analytical skills. A commitment to fostering and upholding an inclusive work environment.
Preferred Qualifications
Minimum of five (5) years of experience in statistics, statistical methods, and statistical software. Experience leading projects and setting the technical direction. Prior publication of high-quality peer-reviewed research articles. Experience in one or more of the following: Domain knowledge in biomedical informatics, healthcare, or a related field Strong programming skills in Python, experience with machine learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with cloud services ( AWS , GCP , Azure). Experience using statistical software for analyses (e.g., Stata, SAS , R). Familiarity with biostatistics or principles of analyzing public health data. Experience working with and deploying machine learning models Experience providing data management and analytic support for complex surveys, longitudinal cohort studies, and/or randomized controlled trials. Data ingestion pipelines, data analysis, data visualization and the ability to learn other programming languages as needed
Description of Job Duty
Design, development and delivery of machine learning and deep learning solutions, including problem definition, data acquisition, exploration, training, testing, and evaluating machine learning models, and creating end-to-end pipelines and solutions in production. Manage multiple initiatives to create and improve the CVRI’s AI’s models and analytics. Responsible for working across the entire machine learning pipeline, including data exploration, feature engineering, model training, deployment, monitoring, and calibration/retraining. Collaborate closely with research faculty and staff, such as project managers, graphic artists, UX designers, other developers, systems analysts and sales and marketing professionals. Develop automated systems and tools to process, clean, and verify data integrity. Provide analysis and support data interpretation to both technical expert and lay users of public health data that include structured and unstructured data, such as free text, images, and data of mixed types. Assist in monitoring data quality issues as they relate to user data products, and collaborate with Information
