Company

The University Of TennesseeSee more

addressAddressKnoxville, TN
type Form of workFull-Time
CategorySales/marketing

Job description

Postdoctoral Researcher - Machine Learning and Big Data in Electronic Health Records and Other High Consequence Applications

About the Position:

We are seeking a highly motivated and skilled Postdoctoral Researcher to join our dynamic team and contribute to cutting-edge research in the field of machine learning and big data applied to electronic health records (EHRs). As a Postdoctoral Researcher, you will play a crucial role in advancing our understanding of how machine learning and big data analytics can transform healthcare by extracting valuable insights from vast and diverse EHR datasets. This position offers an exciting opportunity to collaborate with interdisciplinary experts, leverage state-of-the-art technologies, and significantly impact the future of healthcare and other high-consequence applications. US citizenship is a prerequisite.

Responsibilities:

The role involves a broad spectrum of responsibilities, merging innovative research methodologies with advanced technology application and leadership in high-consequence domains. The successful candidate will support some or all of the following depending on skills and experience:

Research and Development:

  • Conduct innovative research to develop novel algorithms, models, and techniques using machine learning and big data methods, with applications ranging from analyzing electronic health records (EHRs) to broader areas including digital twins and complex systems simulations.
  • Design and implement scalable data pipelines for preprocessing, cleaning, and integrating diverse data sources to create reliable datasets, focusing on both large datasets and those with scarce data.
  • Apply statistical analysis and machine learning techniques to extract valuable insights, identifying patterns, outcomes, predictive models, and recommendations tailored to specific domains.
  • Conduct research and technology application development in machine learning/AI, digital twins, and computer simulations for complex processes and operations.

Collaboration and Leadership:

  • Collaborate with professionals, domain experts, and partner organizations to identify research questions and translate them into actionable solutions.
  • Play a leadership role in the conceptualization and implementation of simulation engineering, supporting the setup and expansion of laboratory facilities
  • Work independently and as part of a team, providing leadership and direction to junior researchers, students, and postdocs.
  • Confers with principal investigators (PI) in developing and executing comprehensive research projects and plans.

Technology and Methodology:

  • Develop complex systems architectures, engage in software engineering (programming), and database interface development.
  • Utilize computer simulations, modeling, and augmented reality/virtual reality (AR/VR) for predictive analytics and "what-if" scenarios.
  • Develop advanced machine learning/AI models for a wide variety of applications.

Communication and Management:

  • Prepare manuscripts, publications, grant proposals, and presentations to disseminate research findings.
  • Coordinate and direct the work of students, postdocs, and less senior researchers, ensuring collaborative and productive research activities.
  • Provide oversight of lab equipment, servers, workstations, and software inventory, serving as a primary expert on the lab's computing operations integration.
  • Responsible for overseeing the lab's computing infrastructure, ensuring lab operations safety, and compliance with relevant standards and regulations.

This comprehensive role is designed for individuals eager to drive forward the state of the art in machine learning, data analytics, and simulation engineering across various critical sectors. The successful candidate will demonstrate a robust capability for independent judgment, leadership, and collaboration, underpinning significant advancements in research and development.

Qualifications:

  • A Ph.D. in Computer Science, Electrical Engineering, Systems Engineering, Biomedical Informatics, or related fields with a focus on machine learning, data science, or healthcare analytics.
  • A strong background in machine learning, deep learning, natural language processing, and statistical data analysis techniques and computational simulation.
  • Experience working with big data technologies, such as Apache Hadoop, Spark, or similar frameworks is desirable but not required
  • Facility with AR/VR technologies and their use as visualization tools is desirable but not required
  • Proficiency in programming languages commonly used in data science, such as Python, R, or Julia.
  • Familiarity with electronic health records and healthcare-related datasets is highly desirable.
  • Strong publication record in relevant conferences and journals, demonstrating expertise in machine learning and healthcare informatics is desirable but not required
  • Excellent problem-solving and critical-thinking skills, with the ability to approach complex challenges with creativity and innovation.
  • Effective communication skills, both written and verbal, to articulate research findings and collaborate with a diverse team of researchers and professionals.
  • Demonstrated ability to work independently and collaboratively, showing initiative and a passion for advancing research in the healthcare domain.
  • Willingness to aggressively purse publication and grant writing

Duration and Compensation:

This is a full-time, fixed-term position with a duration of up to 2 years. The successful candidate will receive a competitive salary and benefits package commensurate with experience and qualifications.

Application Instructions:

Interested applicants should submit a cover letter, updated curriculum vitae, a list of publications, and the names and contact information of at least two academic or professional references. Please outline your relevant research experience and your interest in contributing to the field of machine learning and big data applied to electronic health records. Applications will be reviewed on a rolling basis until the position is filled. This position is limited to US citizens.

Organization Information:

The University of Tennessee Applied Systems Laboratory is a new organization that supports high-consequence environments with machine learning, and complex systems simulation research.

Refer code: 8762283. The University Of Tennessee - The previous day - 2024-03-27 23:32

The University Of Tennessee

Knoxville, TN
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