The School of Computing at Queen’s University invites applications from suitably qualified candidates interested in teaching courses shown below.
The University invites applications from all qualified individuals. Queen’s University is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, aboriginal people, persons with disabilities, and persons of any sexual orientation or gender identity. All qualified candidates are encouraged to apply; however, Canadians and permanent residents will be given priority.
Applications will be received until March 31, 2022. Review of applications will commence shortly thereafter, and the final appointment is subject to budgetary approval. Additional information about the School of Computing can be found at http://www.queensu.ca
Courses available are listed below.
To apply as a Term Adjunct, see: http://flux.cs.queensu.ca/employment/applying-for-a-term-adjunct-position/
To apply as a Teaching Fellow, see: http://flux.cs.queensu.ca/employment/applying-for-a-teaching-follow-position/
Academic Year 2022/2023 Fall Term
This spring term period is from September 1, 2022 to December 31, 2022.
Applications will be received until March 31, 2022.
CISC 110 Creative Computing Units: 3.00
Introduction to fundamental programming concepts in the context of visual, interactive media. Students may develop applications in any domain (e.g., fine art, education, commerce, physical or social sciences) while learning about algorithms, program design, logic, program control flow, functions, testing, etc.
NOTE No computing or art background required.
NOTE Sufficient preparation for CISC 121/3.0. . Alternative to CISC 151/3.0. With permission of the School, students with programming experience may take this concurrently with CISC 121/3.0
LEARNING HOURS 120 (36L;84P)
Requirements: Exclusion No more than 3.0 units from APSC142;APSC143;CISC101; CISC110; CISC151. One-Way Exclusion May not be taken with or after: CISC121; CISC or SOFT at the 200 level and above.
Course Equivalencies: CISC 101/110/121 / APSC 143
CISC 121 Introduction to Computing Science I Units: 3.00
Introduction to design, analysis, and implementation of algorithms. Recursion, backtracking, and exits. Sequences. Elementary searching and sorting. Order-of-magnitude complexity. Documentation, iterative program development, translating natural language to code, testing and debugging.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P
RECOMMENDATION Some programming experience (such as high-school level programming or CISC 101/3.0 or CISC 110/3.0 or CISC 151/3.0
Requirements: Prerequisite None. Corequisite (CISC 102 or MATH 110 or MATH 111 or MATH 112 or MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126 or APSC 171 or APSC 172 or APSC 174 or COMM 161 or COMM 162).
CISC 235 Data Structures Units: 3.00
Design and implementation of advanced data structures and related algorithms, including correctness and complexity analysis.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 124 and CISC 203).
CISC 324 Operating Systems Units: 3.00
Layered operating systems for conventional shared memory computers: concurrent processes. Synchronization and communication. Concurrent algorithms. Scheduling. Deadlock. Memory management. Protection. File systems. Device management. Typical layers.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 221 and CISC 235).
CISC 365 Algorithms I Units: 3.00
Principles of design, analysis and implementation of efficient algorithms. Case studies from a variety of areas illustrate divide and conquer methods, the greedy approach, branch and bound algorithms and dynamic programming.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 203 and CISC 204 and CISC 235).
CISC 371 Nonlinear Data Analysis Units: 3.00
Methods for nonlinear data analysis, particularly using numerical optimization. Applications may include: unconstrained data optimization; linear equality constraints; constrained data regression; constrained data classification; evaluating the effectiveness of analysis methods.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 271 and [STAT 263 or STAT_Options]). Exclusion CISC 351.
CISC 451 Topics in Data Analytics Units: 3.00
Content will vary from year to year; typical areas covered may include: tools for large scale data analytics (Hadoop, Spark), data analytics in the cloud, properties of large scale social networks, applications of data analytics in security.
LEARNING HOURS 120 (36I;36Lb;48P)
Requirements: Prerequisite A minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 333 or CISC 351 or CISC 372).
CISC 471 Computational Biology Units: 3.00
Advanced computational approaches to the problems in molecular biology. Techniques and algorithms for sequence analysis and alignment; molecular databases; protein structure prediction and molecular data mining.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 271 and CISC 352 and CISC 365).
COGS 100 Introduction to Cognitive Science Units: 3.00
A multidisciplinary approach to the study of the mind combining approached from philosophy, psychology, linguistics, neuroscience, anthropology, and artificial intelligence. Logic, rules, concepts, and other mental representations used to generate thought and behaviour. Implementation of computational and cognitive models of mental processes.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite None.
Academic Year 2022/2023 Winter Term
This summer term period is from January 1, 2023 to April 31, 2023.
Applications will be received until March 31, 2022.
CISC 101 Elements of Computing Science Units: 3.00
Introduction to algorithms: their definition, design, coding, and execution on computers. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary. Sufficient preparation for CISC 121; alternative to CISC 110/3.0 and CISC 151/3.0
LEARNING HOURS 120(36L;84P)
Requirements: Prerequisite None. Exclusion APSC 142; APSC 143; CISC 110; CISC 151. One-Way Exclusion May not be taken with or after CISC 121; CISC at the 200-level or above.
CISC 121 Introduction to Computing Science I Units: 3.00
Introduction to design, analysis, and implementation of algorithms. Recursion, backtracking, and exits. Sequences. Elementary searching and sorting. Order-of-magnitude complexity. Documentation, iterative program development, translating natural language to code, testing and debugging.
NOTE Also offered online. Consult Arts and Science Online. Learning Hours may vary.
LEARNING HOURS 120 (36L;84P)
RECOMMENDATION Some programming experience (such as high-school level programming or CISC 101/3.0 or CISC 110/3.0 or CISC 151/3.0)
Requirements: Prerequisite None. Corequisite (CISC 102 or MATH 110 or MATH 111 or MATH 112 or MATH 120 or MATH 121 or MATH 123 or MATH 124 or MATH 126 or APSC 171 or APSC 172 or APSC 174 or COMM 161 or COMM 162).
CISC 151 Elements of Computing with Data Analytics Units: 3.00
Introduction to algorithms: their definition, design, coding, and execution on computers, with applications drawn from data analytics, including simple prediction and clustering. Intended for students who have no programming experience. All or most assignment work will be completed during lab time.
NOTE Sufficient preparation for CISC 121/3.0. Alternative to CISC 101/3.0 and CISC 110/3.0
LEARNING HOURS 120(36L;84P)
Requirements: excl 3 fr APSC142;CISC101, CISC110; CISC151 One-Way Exclusion May not be taken with or after CISC121; CISC or SOFT courses at the 200-level and above.
CISC 226 Game Design Units: 3.00
An introduction to techniques for designing elementary computer games. Topics will include game development tools and processes, principles of game design, game prototyping and game evaluation.
LEARNING HOURS 120 (36L;60G;24P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 124.
CISC 235 Data Structures Units: 3.00
Design and implementation of advanced data structures and related algorithms, including correctness and complexity analysis.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 124 and CISC 203).
CISC 324 Operating Systems Units: 3.00
Layered operating systems for conventional shared memory computers: concurrent processes. Synchronization and communication. Concurrent algorithms. Scheduling. Deadlock. Memory management. Protection. File systems. Device management. Typical layers.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 221 and CISC 235).
CISC 472 Medical Informatics Units: 3.00
Current topics in the application of information technology to medical image computing and its use in image-guided medical interventions.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Registration in a School of Computing Plan and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 330.
CISC 492 Topics in Computing III Units: 3.00
Content varies. Not offered every year.
NOTE Learning Hours will vary.
Requirements: Prerequisite Registration in a School of Computing Plan and permission of the instructor.
CISC 497 Social, Ethical and Legal Issues in Computing Units: 3.00
A wide range of topics of current importance in computing, including technical issues, professional questions, and moral and ethical decisions. Students make presentations, deliver papers, and engage in discussion.
LEARNING HOURS 120 (12L;24S;84P)
Requirements: Prerequisite Level 4 or above and registration in a COMP Major or Specialization Plan and a cumulative GPA of 1.90 and a (GPA of 2.60 in CISC; COCA; COGS; SOFT) and (30.0 units of CISC; COCA; COGS; SOFT) and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 352 or CISC 365).
COGS 201 Cognition and Computation Units: 3.00
Introduction to the computational aspects of the mind. Implementation of computer programs for reasoning, decision making, and problem solving to understand these mental processes. Information theory and behaviourism; computational models of cognition, perception and memory processes demonstrating modeling approaches, and cognitive architectures.
LEARNING HOURS 120 (36L;84P)
Requirements: Prerequisite Level 2 or above and a minimum grade of a C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (COGS 100 or PSYC 100). Exclusion COGS 200; PSYC 220.
