Part-Time Programmer Analysts
Location: Penn State University Park
Time Type: Part time
Job Description
APPLICATION INSTRUCTIONS:
CURRENT PENN STATE EMPLOYEE (faculty, staff, technical service, or student), please login to Workday to complete the internal application process. Please do not apply here, apply internally through Workday.
CURRENT PENN STATE STUDENT (not employed previously at the university) and seeking employment with Penn State, please login to Workday to complete the student application process. Please do not apply here, apply internally through Workday.
If you are NOT a current employee or student, please click “Apply” and complete the application process for external applicants.
Approval of remote and hybrid work is not guaranteed regardless of work location. For additional information on remote work at Penn State, see Notice to Out of State Applicants.
JOB DESCRIPTION AND POSITION REQUIREMENTS
The Department of Computer Science and Engineering is seeking part-time Programmer Analysts to support an NIH National Center for Advancing Translational Science-funded project called: “The Biomedical Data Translator.” https://ncats.nih.gov/research/research-activities/translator
These programmers will develop the following components to be incorporated into the ARAX (https://github.com/RTXteam/RTX) system: Implement statistical and machine learning techniques to augment graph edge properties in ARAX; Create modular python wrappers to interface with NCATS (National Center for Advancing Translational Services) translator API (Application Programming Interface) endpoints (https://smart-api.info/registry) and UI (https://ui.transltr.io/) to allow ingestion of open access data into (and from) the ARAX system; Implement automated thresholding of ARAX filtering components; Create a modular, tunable weighting scheme for scoring and ranking of results to be returned by the ARAX system; Train a graph node embedding + random forest model on open access clinical and biomedical data to extend current capabilities for predicting the probability that a drug treats a disease; Maintain the ARAX code base to retain compliance with API and data standardization version updates as specified by the advisory, API, and data modeling committees; Address additional ARAX code-base issues as they are identified and assigned by faculty member.
Requirements include:
- Excellent interpersonal and communication skills
- Strong attention to detail
- Master’s degree plus two years of related experience, or an equivalent combination of education and experience
- Specific skills required are experience with the Neo4j graph database, interacting with REST APIs, more than three years’ experience with Python, and associated machine learning packages (such as Scikit learn)
- More than three years’ experience with Git and GitHub
- Ability to effectively work remotely with a large team of programmers and scientists
- Two years’ or more experience working with biomedical ontologies/data sets and publicly available databases
Pay and hours per week negotiable within funder restrictions. Please include a cover letter and resume.
BACKGROUND CHECKS/CLEARANCES
Employment with the University will require successful completion of background check(s) in accordance with University policies.
CAMPUS SECURITY CRIME STATISTICS
Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act and the Pennsylvania Act of 1988, Penn State publishes a combined Annual Security and Annual Fire Safety Report (ASR). The ASR includes crime statistics and institutional policies concerning campus security, such as those concerning alcohol and drug use, crime prevention, the reporting of crimes, sexual assault, and other matters. The ASR is available for review here.
EEO IS THE LAW
Penn State is an equal opportunity employer and is committed to providing employment opportunities to all qualified applicants without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status. If you are unable to use our online application process due to an impairment or disability, please contact 814-865-1473.
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