美国贝勒医学院2023年招聘博士后职位（数据分析）

贝勒医学院（Baylor College of Medicine）是美国休斯敦的一所私立医药学校，被认为是全美最杰出的医学院之一，获中国教育部认证。学校在世界范围内的生物医药研究领域处于领先地位，学校最早建立于一九零零年，迄今为止已经有一百多年的悠久历史了。

贝勒医学院为学生提供财政援助和奖学金，帮助学生减轻就学期间的经济压力，符合要求的学生都可以申请奖学金和财政援助。学校致力于医药和研究生教育，并且因而获得了超过一亿美金的捐赠，是美国六十三所获得超过一亿捐赠的优秀大学之一。

Postdoctoral Associate- Data Analysis

Baylor College of Medicine

Job Description

Summary

We are seeking a dedicated and innovative Postdoctoral fellow to work on the standardization of laboratory test names and laboratory test stewardship. Laboratory test names vary widely among hospitals and can be confusing. The work of this position will be aligned with the goals of TRUU-Lab, a national initiative to generate laboratory tests names that are easily understood by clinicians, and which reduce medical errors. Optimized names will be created through analysis of clinician survey data, by testing order names in mock EMR systems, and by the utilization of artificial intelligence (AI) and large language models to generate novel names that follow standard best practices. This position also entails writing papers and grants that will further our mission of helping clinicians order the right laboratory test, at the right time, for the right patient. This position is currently for 12 months, and could be extended further contingent on grant support.

Job Duties

· Collaborates with the TRUU-Lab team, consisting of healthcare professionals, CDC, FDA, EMR vendors, instrumentation vendors, programmers, and computer scientists to advance projects related to laboratory test name standardization.

· Designs, conducts, and analyzes experiments related to laboratory test ordering.

· Helps create standardized laboratory test names that can be used nationally.

· Helps create test naming guidelines.

· Applies statistical techniques to interpret research data from test naming surveys.

· Supervises the collection of data from Electronic Medical Records (EMR) databases.

· Collaborates with AI experts to use large language models to generate better test names.

· Plays an active role in the development of grant proposals.

· Prepares research findings for publication.

· Stays current with relevant advancements in laboratory medicine and data science by attending seminars

Minimum Qualifications

· MD or Ph.D. in Basic Science, Health Science, or a related field.

· No experience required.

Preferred Qualifications

· Ph.D. in Data Science, or fields related to Laboratory Medicine (Clinical Chemistry, Microbiology, etc.); Doctorate in Clinical Laboratory Science (DCLS), or MD or equivalent.

· Strong research background with a track record of relevant publications.

· Proficiency in statistical analysis, and use of R, SPSS, SAS software and data visualization tools.

· Experience working with electronic medical records.

· Strong background in laboratory medicine and test utilization highly desirable.

· Familiarity with artificial intelligence and machine learning concepts.

· Excellent communication skills, both written and verbal.

· Demonstrated ability in grant writing and securing research funding is a plus.

· Highly motivated, organized, and capable of working independently. Effective teamwork and collaboration skills.

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