The Department of Computational Medicine & Bioinformatics at the University of Michigan-Ann Arbor is inviting applications for a Lecturer III position for Fall Term 2023 and Winter Term 2024 to assist in teaching Bioinformatics 575 and Bioinformatics 527. The courses will be taught in person at the Ann Arbor campus and meet Monday through Thursday for classroom lectures as well as hands-on laboratory sessions. The successful candidate will be mentored by two Lecturer IV faculty who serve as the course directors and will guide the successful candidate as they participate in teaching and advising students in the growing Bioinformatics Master's program.
BIOINF527 : Students will be introduced to the fundamental theories and practices of Bioinformatics through a series of integrated lectures and labs. A broad range of topics will be covered illustrating how bioinformatics is shaping the modern landscape of biomedical research. Students develop practical skills for processing, visualizing, and analyzing high-throughput biomedical data.
BIOINF575 : Programming Laboratory in Bioinformatics - This course introduces the principles of general computer programming and relational databases as tools to solve problems in bioinformatics data analysis. General programming and graph generation is taught using the object oriented language Python but some variations may occur. The relational database language SQL is taught in conjunction with database design, construction and querying. Packages that extend the capabilities of Python are explored. Grades are based on homework, quizzes, participation in class discussions, and cooperative development of a group project or homework.
A successful candidate will have expertise in either Python or R programming and also be comfortable working from the command line. Master's degree in Biostatistics, Statistics or Bioinformatics or a related field is required. A PhD degree will be considered as a plus. Relevant teaching experience and evidence of teaching excellence are desirable. Candidates will be evaluated based on submitted CV, teaching evaluations, and relevant recommendations.
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