Postdoctoral Associate

1 month ago


Houston, Texas, United States Baylor College of Medicine (BCM) Full time

This position is located within IQuESt, the Center for Innovations in Quality, Effectiveness and Safety. We are the largest center for Health Services Research within the Southwest. We conduct high-quality scientific research that improves the health of patients across the nation, by helping to ensure the patient-centered delivery of scientific discoveries. We are looking for a Postdoctoral Associate to collaborate on data science projects with utility experts. We work on projects like health risk assessment, predicting adverse outcomes, signal processing and natural language processing (NLP). The ideal candidate will have significant experience using Python, and R, R Shiny, and MATLAB in multiple analytical applications, such as nonlinear time series analysis, machine learning (for example, binomial/regression models or ensemble models), deep learning (for example, NN, CNN, and RNN), and probability, statistics, and NLP. As with any successful analytics project, it all starts with the data, so you should have experience extracting and transforming data from relational databases, i.e. SQL Server.

You'll be a full-time member of our data science team. As a Data Scientist, you will be responsible for finding creative solutions to challenges faced by clinical investigators to solve healthcare challenges through evidence based approach. These solutions will be found by introducing machine learning and other data science concepts and building applications within a scripting language, such as Python, R, etc. You will engage with clinical collaborators to fully understand their clinical questions and process flows to make sure the solution that is provided to them will address the challenges successfully.

The ideal candidate has a MS, or PhD in computer science, math, engineering, stats, or data science. You should have a proven track record of efficiently conducting and coordinating data analytics projects both independently and collaboratively over at least a two-year period for junior positions or a five-year period for senior positions. Exceptional educational or industry experience can offset any particular requirement. A background in a diverse field that complements data science (such as applied discipline expertise and statistics) is considered an asset.

Job Duties
  • Develops dashboards, calculations and reports which may require programming in SQL and the like.
  • Performs data management in SQL and develops and tunes machine learning models, which may require programming in Python and/or R.
  • Prepares comprehensive documented observations, analyses and interpretations of results including technical reports, summaries, protocols and quantitative analyses
  • Translates healthcare challenges into mathematical problems (Requirement and Scope definition).
  • Documents the applications that are developed.
  • Conducts regular progress meetings with clinical collaborators (multiple times a week) face to face or via on-line meeting software. This may include working on-site. Pending COVID-19 travel and working restrictions.
  • Works with researchers and clinicians to design and implement new NLP components and prepare presentations and publications.
  • Develops infrastructure for cleaning and processing data and runs experiments to evaluate system performance.
  • Performs error analysis and suggesting and implements improvements.
  • Performs testing, debugging, and hardening complex pipelines of NLP components.
  • Performs other job-related duties as assigned.
Minimum Qualifications
  • MD or Ph.D. in Basic Science, Health Science, or a related field.
  • No experience required.
Preferred Qualifications
  • Experience participating in the research process in an academic setting.
  • Experience applying machine learning to NLP problems.
  • Expertise in MATLAB or R or Python or SAS Expertise in SQL.
  • Degree in Quantitative field such as Computer Science or a related field.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.


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