Assistant Professor-Mathematical Sciences - Remote | WFH
Assistant Professor-Mathematical Sciences - Remote | WFH
Get It Recruit - Educational Services
Melrose, MT
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We invite applications for a tenure-track faculty position in Data Science. The successful candidate will join a dynamic team committed to excellence in teaching and research within the INBRE network. This position offers a competitive benefits package including health, dental, and vision insurance, a mandatory retirement plan with employer contribution, partial tuition waiver, and a wellness program.
Responsibilities
Teach 3-6 credits per semester, up to 9 credits per year.
Conduct research within the INBRE network focusing on Data Science.
Organize professional development workshops on Data Science techniques.
Advise Data Science majors, oversee capstone projects, and contribute to curriculum design.
Required Qualifications
PhD in Data Science, Mathematics, Statistics, or a related field awarded by August 2024.
Expertise in data science areas such as machine/deep learning, big data mining and analytics, data visualization, statistical learning, etc.
Proficiency in Python and R for teaching purposes.
Strong oral and written communication skills.
Preferred Qualifications
Prior experience teaching college-level mathematics, statistics, and/or Data Science courses.
Experience working with health-related data.
Application Requirements
To be considered, please submit the following:
Cover Letter Addressing Qualifications.
Resume.
Contact information for 3 professional references.
One-page statement of current research interests.
List of courses taught in the past three years.
Copies of graduate transcripts (unofficial transcripts acceptable).
Additional Information
Applications received by July 15, 2024, will receive full review and consideration.
An offer of employment is contingent upon a satisfactory criminal background check.
We are committed to diversity and inclusion. We encourage applications from qualified minorities, women, veterans, and individuals with disabilities.
Veterans are encouraged to apply and may claim veteran's preference by completing the employment preference form.
Why Work?
Join us in advancing science, engineering, and technology to meet the changing needs of society. Enjoy a supportive work environment, comprehensive benefits, and opportunities for professional development.
Employment Type: Full-Time
Responsibilities
Teach 3-6 credits per semester, up to 9 credits per year.
Conduct research within the INBRE network focusing on Data Science.
Organize professional development workshops on Data Science techniques.
Advise Data Science majors, oversee capstone projects, and contribute to curriculum design.
Required Qualifications
PhD in Data Science, Mathematics, Statistics, or a related field awarded by August 2024.
Expertise in data science areas such as machine/deep learning, big data mining and analytics, data visualization, statistical learning, etc.
Proficiency in Python and R for teaching purposes.
Strong oral and written communication skills.
Preferred Qualifications
Prior experience teaching college-level mathematics, statistics, and/or Data Science courses.
Experience working with health-related data.
Application Requirements
To be considered, please submit the following:
Cover Letter Addressing Qualifications.
Resume.
Contact information for 3 professional references.
One-page statement of current research interests.
List of courses taught in the past three years.
Copies of graduate transcripts (unofficial transcripts acceptable).
Additional Information
Applications received by July 15, 2024, will receive full review and consideration.
An offer of employment is contingent upon a satisfactory criminal background check.
We are committed to diversity and inclusion. We encourage applications from qualified minorities, women, veterans, and individuals with disabilities.
Veterans are encouraged to apply and may claim veteran's preference by completing the employment preference form.
Why Work?
Join us in advancing science, engineering, and technology to meet the changing needs of society. Enjoy a supportive work environment, comprehensive benefits, and opportunities for professional development.
Employment Type: Full-Time
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Seniority level
Entry level -
Employment type
Full-time -
Job function
Education and Training -
Industries
Human Resources Services
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