CS 311: Data Structures and Algorithms (Fall 2026) - Extended Learning

CS 311: Data Structures and Algorithms (Fall 2026) - Extended Learning Apply now Job no: 557452 Work type: Instructional Faculty - Temporary/Lecturer Location: San Marcos Categories: Unit 3 - CFA - California Faculty Association, Temporary, Part Time, Faculty - Computer Science CS 311: DATA STRUCTURES AND ALGORITHMS Semester: Fall 2026 Day/Time: Schedule TBD Modality: In-Person College: College of Science, Technology, Engineering and Mathematics Department: Computer Science, BS CIS Chula Vista through Extended Learning The Department of Computer Science at California State University San Marcos seeks a part-time lecturer for the Bachelor of Computer Information Systems Chula Vista program to teach CS 311: Data Structures and Algorithms. This 16-week course will be taught in-person, from 8/31-12/12/26, schedule TBD. Course Description Teaches a thorough understanding of several advanced methods for implementing the abstract data types and the time used by each method. Includes abstract data types such as dictionary, priority queues, matrices, balanced trees, graphs, and relations, as well as foundation of recursive algorithms, complexity analysis, complexity classes, sorting and searching, computability and undecidability, problem-solving strategies, and heuristic approaches. A Bachelor of Science Degree Experience teaching or equivalent practical experience in Computer Science using a variety of technologies and tools Communication and Presentation Skills Course Design (can design a well-structured syllabus and select appropriate course materials and/or adapt existing course materials for current course section) Continuous Learning and Adaptability (commitment to staying update with latest techniques and developments) Per the California State University’s Out-of-State Employment Policy, the CSU is prohibited from hiring employees to perform CSU-related work outside California. Working in the State of California is a condition of employment. Preferred qualifications: A Master of Science degree, or related field or equivalent and/or equivalent industry experience Experience teaching or mentoring students/employees in topics related to tools and technologies used in Computer Science. The candidate will have experience teaching, either as a course instructor or teaching assistant, especially in topics related to Data Structure and Algorithm. Preference will be given to applicants who demonstrate intercultural competence and a commitment to serving a diverse campus community as it relates to teaching and, as applicable, service. Salary commensurate with degree level and experience Anticipated Hiring Salary: $2,279 per Weighted Teaching Unit (WTU) CSU Classification Salary: $2,279 per Weighted Teaching Unit (WTU) Application : To apply, please prepare to submit the following: Your completed faculty application Curriculum Vitae (uploaded) Contact information for three current references Letter of interest (uploaded) Timeline : A review of applications will begin on May 13, 2026; however, the position will remain open until filled. California State University San Marcos is an Equal Opportunity Employer strongly committed to promoting diversity in all areas of the campus community. We consider qualified applicants for employment without regard to age, physical or mental disability, gender or sex, genetic information, gender identity, gender expression, marital status, medical condition, nationality, race or ethnicity, religion or religious creed, sexual orientation and veteran or military status. Per the California State University’s Out-of-State Employment Policy, the CSU is prohibited from hiring employees to perform CSU-related work outside California. Working in the State of California is a condition of employment. The Department of Computer Science at California State University San Marcos (Temecula Campus) seeks a part-time lecturer for Fall 2026 to teach CS 311: Data Structures and Algorithms. Teaches a thorough understanding of several advanced methods for implementing the abstract data types and the time used by each method. Includes abstract data types such as dictionary, priority queues, matrices, balanced trees, graphs, and relations, as well as foundation of recursive algorithms, complexity analysis, complexity classes, sorting and searching, computability and undecidability, problem-solving strategies, and heuristic approaches. #J-18808-Ljbffr The California State University