Teaching Positions Available for the School of Computing – 2021-22 Academic Year

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 April 30, 2021. 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 2021/2022 Fall Term

This fall term period is from September 1, 2021 to December 31, 2021.

Classes will be in session from September 7, 2021 to December 3, 2021.

Applications will be received until April 30, 2021.



CISC 110/3.0 Creative Computing
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. Sufficient preparation for CISC 121/3.0. Alternative to CISC 101/3.0 and 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)
EXCLUSIONS APSC 142/3.0; APSC 143/3.0; CISC 101/3.0; CISC 151/3.0
ONE-WAY EXCLUSION May not be taken with or after CISC 121/3.0 or CISC at the 200-level or above.


CISC 282/3.0 Fundamentals of Web Development
This course surveys current best practices for implementing attractive, usable, secure and maintainable web applications. Other issues considered include: accessibility, platform and browser independence, licensing of intellectual property, scalability, user privacy, and using web technologies in mobile development.
LEARNING HOURS 120 (36L;48O;36P)
PREREQUISITE Level 2 and C– (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 124/3.0.
EQUIVALENCY CISC P82/3.0.


CISC 422/3.0 Formal Methods in Software Engineering
Mathematical methods for describing software behaviour and structure. Topics include (but are not limited to) the following: Requirements specification. Module specification: axiomatic, algebraic, and trace specifications. Abstract models. Verification. Specification-based validation.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Level 4 and registration in a School of Computing Plan and C– (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 223/3.0.


CISC 451/3.0 Topics in Data Analytics
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 (36l;36Lb;48P)
PREREQUISITE C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 333/3.0or CISC 351/3.0 or CISC 372/3.0).


CISC 471/3.0 Computational Biology
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)
PREREQUISITE Registration in a School of Computing Plan and C– (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in [CISC 271/3.0 and CISC 352/3.0 and CISC 365/3.0]


COGS 100/3.0 Introduction to Cognitive Science
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)
ONEWAY EXCLUSION May not be taken with or after CISC 352/3.0; PSYC 200/6.0.

 



Academic Year 2021/2022 Winter Term

This fall term period is from January 1, 2022 to April 30, 2022.

Classes will be in session from January 10, 2022 to April 8, 2022.

Applications will be received until April 30, 2021.



CISC 151/3.0 Elements of Computing with Data Analytics
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)
EXCLUSIONS APSC 142/3.0; APSC 143/3.0; CISC 101/3.0; CISC 110/3.0
ONE-WAY EXCLUSION May not be taken with or after CISC 121/3.0; CISC; SOFT at the 200-level and above.


CISC 223/3.0 Software Specifications
Introduction to techniques for specifying the behaviour of software, with applications of these techniques to design, verification and construction of software. Logic-based techniques such as loop invariants and class invariants. Automata and grammar-based techniques, with applications to scanners, parsers, user-interface dialogs and embedded systems. Computability issues in software specifications.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Level 2 or above and C– (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 124/3.0 andCISC 204/3.0).


CISC 454/3.0Computer Graphics
Introduction to computer graphics, including a review of current hardware; modelling and transformations in two and three dimensions; visual realism: perspective, hidden surface elimination, and shading; colour models; applications in several fields.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Level 3 or above and registration in a School of Computing Plan and C- (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in [CISC 235/3.0 and (MATH 110/6.0 or MATH 111/6.0 or MATH 112/3.0)].


CISC 458/3.0 Programming Language Processors
Introduction to the systematic construction of a compiler: grammars and languages, scanners, top-down and bottom-up parsing, runtime organization, symbol tables, internal representations; Polish notation, syntax trees, semantic routines, storage allocation, code generation, interpreters.
LEARNING HOURS 120 (36L;36Lb;48G)
PREREQUISITE Registration in a School of Computing Plan and C– (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in (CISC 121/3.0 and CISC 221/3.0 and CISC 223/3.0).


CISC 472/3.0 Medical Informatics
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)
PREREQUISITE Registration in a School of Computing Plan and C– (obtained in any term) or a ‘Pass’ (obtained in Winter 2020) in CISC 330/3.0.


CISC 492/3.0 Topics in Computing Science III
Interdisciplinary course in entrepreneurship and software development. Student teams write a business plan and complete a significant programming project. Course topics will include methods to create and evaluate new software enterprises.
PREREQUISITE CISC 235, COMM 200, or permission of the instructor


COGS 201/3.0 Cognition and Computation
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)
PREREQUISITE Level 2 or above and C(taken in any term) or a Pass(obtained in Winter 2020) in (COGS 100/3.0 or PSYC 100/6.0).
EXCLUSIONS COGS 200/6.0; PSYC220/6.0


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