University of Missouri-Saint Louis
ASSISTANT TEACHING PROFESSOR
University of Missouri-Saint Louis, Saint Louis, Missouri, United States, 63146
Job ID:
52332Location:
St. LouisFull/Part Time:
Full-TimeHiring Department:
UMSL GEOSPATIALJob Description
The UMSL Geospatial Collaborative invites applications for a non-tenure track Assistant Professor position in Geospatial Science. The successful candidate will play a key role in advancing the Collaborative's mission to provide high-quality education, research, and community engagement in geospatial science and technology across all disciplines. This position is a full-time appointment with an initial contract of two years, renewable based on performance and funding availability.Key Responsibilities:Teaching (80%):
Develop and teach undergraduate and graduate courses in geospatial science, including but not limited to GIS, remote sensing, spatial analysis, cartography, and geospatial programming (7 courses per academic year).Incorporate innovative teaching methods and technologies to enhance student learning and engagement.Advise and mentor students on academic and career pathways in geospatial science.
Service (20%):
Participate in the Geospatial Collaborative, college, and university committees and initiatives.Engage with the geospatial community through outreach activities, partnerships, and professional organizations.Contribute to the development and implementation of the Collaborative's strategic goals.
Research and Scholarship:
Research is not required, but the selected candidate has the option to:
Engage in collaborative research projects within the UMSL Geospatial Collaborative and with external partners.Pursue and secure external funding to support research initiatives.Publish research findings in peer-reviewed journals and present at professional conferences.
Applicants must be authorized to work in the United States. The University will not sponsor applicants for this position for employment visas.Qualifications
A Ph.D. in Geospatial Science, GIScience, Remote Sensing, Computer Science or a closely related field.Demonstrated excellence in teaching and a commitment to student success.Experience with GIS software (e.g., ArcGIS), remote sensing (e.g., ENVI, ERDAS Imagine), and geospatial programming languages (e.g., Python, R).Experience in Machine Learning and AI.Experience with online and hybrid course delivery.Ability to work collaboratively with diverse groups, including students, faculty, industry partners, and community stakeholders.Excellent communication and interpersonal skills.Application Materials
Submit online application that includes a cover letter, Curriculum Vitae, and three Letters of Recommendation:
https://erecruit.umsystem.edu/Inquiries can be directed to Dr. Reda Amer at
reda.amer@umsl.edu .Other Information
The mission of the UMSL Geospatial Collaborative is to provide the geospatial knowledge to UMSL faculty and students, and to foster geospatial research across all disciplines. By leveraging advanced geospatial technologies and methodologies, the Collaborative aims to enhance educational outcomes and support innovative research initiatives.Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses. For additional information on University benefits, please visit the Faculty & Staff Benefits website at
https://www.umsystem.edu/totalrewards/benefits .Values Commitment:
We value the uniqueness of every individual and strive to ensure each person's success. Contributions from individuals with diverse backgrounds, experiences and perspectives promote intellectual pluralism and enable us to achieve the excellence that we seek in learning, research and engagement.Equal Employment Opportunity:
The University of Missouri System is an Equal Opportunity Employer. Equal Opportunity is and shall be provided for all employees and applicants for employment on the basis of their demonstrated ability and competence without unlawful discrimination.
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52332Location:
St. LouisFull/Part Time:
Full-TimeHiring Department:
UMSL GEOSPATIALJob Description
The UMSL Geospatial Collaborative invites applications for a non-tenure track Assistant Professor position in Geospatial Science. The successful candidate will play a key role in advancing the Collaborative's mission to provide high-quality education, research, and community engagement in geospatial science and technology across all disciplines. This position is a full-time appointment with an initial contract of two years, renewable based on performance and funding availability.Key Responsibilities:Teaching (80%):
Develop and teach undergraduate and graduate courses in geospatial science, including but not limited to GIS, remote sensing, spatial analysis, cartography, and geospatial programming (7 courses per academic year).Incorporate innovative teaching methods and technologies to enhance student learning and engagement.Advise and mentor students on academic and career pathways in geospatial science.
Service (20%):
Participate in the Geospatial Collaborative, college, and university committees and initiatives.Engage with the geospatial community through outreach activities, partnerships, and professional organizations.Contribute to the development and implementation of the Collaborative's strategic goals.
Research and Scholarship:
Research is not required, but the selected candidate has the option to:
Engage in collaborative research projects within the UMSL Geospatial Collaborative and with external partners.Pursue and secure external funding to support research initiatives.Publish research findings in peer-reviewed journals and present at professional conferences.
Applicants must be authorized to work in the United States. The University will not sponsor applicants for this position for employment visas.Qualifications
A Ph.D. in Geospatial Science, GIScience, Remote Sensing, Computer Science or a closely related field.Demonstrated excellence in teaching and a commitment to student success.Experience with GIS software (e.g., ArcGIS), remote sensing (e.g., ENVI, ERDAS Imagine), and geospatial programming languages (e.g., Python, R).Experience in Machine Learning and AI.Experience with online and hybrid course delivery.Ability to work collaboratively with diverse groups, including students, faculty, industry partners, and community stakeholders.Excellent communication and interpersonal skills.Application Materials
Submit online application that includes a cover letter, Curriculum Vitae, and three Letters of Recommendation:
https://erecruit.umsystem.edu/Inquiries can be directed to Dr. Reda Amer at
reda.amer@umsl.edu .Other Information
The mission of the UMSL Geospatial Collaborative is to provide the geospatial knowledge to UMSL faculty and students, and to foster geospatial research across all disciplines. By leveraging advanced geospatial technologies and methodologies, the Collaborative aims to enhance educational outcomes and support innovative research initiatives.Benefit Eligibility
This position is eligible for University benefits. As part of your total compensation, the University offers a comprehensive benefits package, including medical, dental and vision plans, retirement, and educational fee discounts for all four UM System campuses. For additional information on University benefits, please visit the Faculty & Staff Benefits website at
https://www.umsystem.edu/totalrewards/benefits .Values Commitment:
We value the uniqueness of every individual and strive to ensure each person's success. Contributions from individuals with diverse backgrounds, experiences and perspectives promote intellectual pluralism and enable us to achieve the excellence that we seek in learning, research and engagement.Equal Employment Opportunity:
The University of Missouri System is an Equal Opportunity Employer. Equal Opportunity is and shall be provided for all employees and applicants for employment on the basis of their demonstrated ability and competence without unlawful discrimination.
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