Missouri-Columbia: Instructor for Data Science in the Life Sciences
Position description:
The Division of Plant Science and Technology (DPST) in the College of Agriculture, Food and Natural Resources (CAFNR) at the University of Missouri (MU) seeks an Instructor for Data Science in the Life Sciences. The position is a 9-month non-tenure-track faculty position. Data science is crucial to advance the field of plant biology and tackle global challenges such as climate change and food security. With the increasing volume and complexity of biological and -omics data, understanding and enabling data science techniques is a requisite to analyze and interpret large datasets more efficiently. Our division is committed to training the next generation of scientists and is planning to integrate data science into our undergraduate and graduate plant science curriculum. We are recruiting an effective instructor, who will design and teach data science modules with an emphasis in the life sciences and plant biology.
responsibilities:
Primary responsibility will be to develop and deliver face-to-face and online courses as part of a new undergraduate/graduate Data Science in the Life Sciences certificate program. The candidate should be able to discuss program goals and to establish clear course and learning objectives. The successful candidate is expected to utilize innovative classroom techniques and methodologies that involve students from different life science disciplines in challenging learning and creative active-learning experiences. The responsibilities also include providing feedback to students that will enhance their academic growth, adapting course objectives and strategies according to student needs and student evaluations, and conducting formative and summative assessments of student learning. As an integral faculty member of DPST, the candidate will collaborate with other teaching faculty of the Division and participate in faculty meetings and committees.
minimum qualifications:
-
A Master’s degree in data science, computer science, informatics, mathematics, statistics, or a related discipline at the time of hire.
Candidates will be evaluated on:
- Demonstrated skills in verbal and written communication.
- Learner-focused orientation and commitment to quality in all aspects related to content delivery.
- Ability to multitask effectively and possess excellent time management and organizational skills.
- Previous experience in any area of life sciences and/or plant sciences Familiarity with SQL, R, Python and other statistical tools.
Application Procedure:
Apply online at http://hrs.missouri.edu/find-a-job/academic/ for Job ID 50307. Please submit:
(1) your resume
(2) a letter of application explaining your suitability for the advertised position
(3) a teaching philosophy and examples of previous teaching experience
(4) and the contact information for at least 3 references.
Contact:
Questions pertaining to the job may be directed to Dr. David Mendoza-Cózatl (mendozacozatld@missouri.edu), Chair of the Search Committee, and Graduate Program Director of DPST. Questions regarding the application process should be directed to Human Resource Services at (573) 882-7976 or muhrs@missouri.edu.
Application Deadline
Candidate screening will begin February 28, 2024, but applications will be accepted until the position is filled.
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 on the basis of their race, color, national origin, ancestry, religion, sex, pregnancy, sexual orientation, gender identity, gender expression, age, disability, or protected veteran status, or any other status protected by applicable state or federal law. This policy applies to all employment decisions including, but not limited to, recruiting, hiring, training, promotions, pay practices, benefits, disciplinary actions and terminations. For more information, visit https://www.umsystem.edu/ums/hr/eeo.