Research Assistant (Part-Time)

Temple University's School of Dentistry is searching for a Part-Time Research Assistant: Big Data Analytics!

As the second-oldest dental school in the U.S., the Maurice H. Kornberg School of Dentistry upholds a legacy of innovation in dental education, research efforts, community service and pioneering healthcare services. Founded in 1863, Kornberg remains a pillar in the dental community. We have more than 7,000 alumni currently redefining the field of oral health around the world. In 2023, the school proudly celebrated its 160th Anniversary.

Kornberg supports health and wellness through a range of diverse educational programs and comprehensive patient services. Our students become dedicated and ethical professionals who honor the traditional models of dental care while staying focused on discovering new ones.
We train the experts who lead the field.

Our renowned faculty and staff provide students with a wealth of opportunities and resources, including smart classrooms, digital dentistry labs, clinics and a preclinical lab that emphasizes collaboration. Students pursue postbaccalaureate, predoctoral, continuing education and advanced education in general dentistry programs.

SALARY RANGE: $20.00 to 22.00 per hour
A variety of important factors are reviewed by HR when considering salary, including job duties, the applicant's education and experience, all relevant internal equity considerations, department budget, and funding source.

*This is a part-time position
*This is a Grant funded position

Position Summary:
The A.I. lab for Dr. Jay Patel within the Kornberg School of Dentistry for Temple University is seeking a part time (20 hours per week) Research Assistant who is highly motivated with strong expertise in big data analytics, machine learning, and deep learning to support ongoing research projects involving large-scale healthcare and biomedical datasets. The Research Assistant will work closely with faculty on data-driven research, model development, and analytics pipelines. Primary responsibilities will include data cleaning, data preprocessing, and data manipulation of large datasets; development, training, and evaluation of machine learning and deep learning models; feature engineering and model optimization; creation of dashboards and data visualizations for research and reporting; documentation of workflows and support for reproducible research; and collaboration with faculty, students, and interdisciplinary research teams. Performs other duties as assigned.

Required Education and Experience:
Bachelor's degree in Computer Science, Data Science, Informatics, Biomedical Informatics, Engineering, or a related computational field and least 6 months experience. An equivalent combination of education and experience may be considered.

Preferred Education and Experience:
*Master's degree
*Familiarity with big data frameworks or cloud/HPC environments is a plus
*Experience in healthcare, biomedical, or EHR/EDR data
*Experience with Python and relevant libraries (e.g., pandas, NumPy, scikit-learn, PyTorch, TensorFlow)

Required Skills and Abilities:
*Must be willing to work part time for at least 20 hours per week.
*Must have a strong background in data analytics, machine learning, and/or deep learning
*Experience working with large, complex datasets
*Must have strong written/verbal communication & interpersonal skills.
*Strong organizational, administrative, and time management skills with strong attention to detail.
*Must have sound judgments with the ability to make independent decision.
*Ability to work with others as part of a collaborative research team.

Essential duties:
*Data cleaning, data preprocessing, and data manipulation of large datasets
*Development, training, and evaluation of machine learning and deep learning models
*Feature engineering and model optimization
*Creation of dashboards and data visualizations for research and reporting
*Documentation of workflows and support for reproducible research
*Collaboration with faculty, students, and interdisciplinary research teams

Temple University is committed to a policy of equal opportunity for all in every aspect of its operations, including employment, service, and educational programs. The University has pledged not to discriminate on the basis of age, color, disability, marital status, national origin or ethnic origin, race, religion, sex (including pregnancy), sexual orientation, gender identity, genetic information or veteran status.

Compliance Statement: In the performance of their functions as detailed in the position description employees have an obligation to avoid ethical, legal, financial and other conflicts of interest to ensure that their actions and outside activities do not conflict with their primary employment responsibilities at the institution. Employees are also expected to understand and be in compliance with applicable laws, University and employment policies and regulations, including NCAA regulations for areas and departments which their essential functions cause them to interact.

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