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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Teaching-Focused Position in Computing: Three (3) Year Term

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for a teaching focused 3-year limited term faculty position at the rank of Assistant or Associate Professor that centres on computer science. The preferred start date for the appointment is August 1, 2021. Salary will be commensurate with qualifications and experience.

Candidates shall have a Ph.D. in computer science or a related discipline completed at the start date of the appointment. Post-secondary teaching, curriculum development and/or other relevant experience is required.

The main criteria for selection are demonstrated commitment to academic and teaching excellence in a post-secondary computing education environment (such as adjunct/sessional lecturing experience), and curriculum development experience. The successful candidate will be expected to demonstrate excellent teaching contributions at both the undergraduate and graduate levels.  A continuing commitment to high quality scholarly work, service and administration is also expected. Support for course development and delivery as well as the scholarship of teaching and learning will be provided to the successful candidate by the Faculty of Arts and Science and through the Queen’s Centre for Teaching and Learning.

The successful candidate will be expected to:

  • work collaboratively in an interdisciplinary and student-focused environment;
  • contribute to academic and pedagogical excellence in support of the programs in the School of Computing; and
  • provide effective service contributions to the School, the Faculty of Arts and Science, the University, and the broader community.

The School of Computing has 32 full-time and 20 cross-appointed faculty, over 800 undergraduate students, and over 150 graduate students. The School offers undergraduate programs in Computer Science, Software Design, Biomedical Computing, Computing and Mathematics, Computing and the Creative Arts and Cognitive Science. The School also offers Master’s, and Doctoral programs in Computer Science.

People from across Canada and around the world come to learn, teach and carry out research at Queen’s University. Faculty and their dependents are eligible for an extensive benefits package including prescription drug coverage, vision care, dental care, long term disability insurance, life insurance and access to the Employee and Family Assistance Program. You will also participate in a pension plan. Tuition assistance is available for qualifying employees, their spouses and dependent children.  Queen’s values families and is pleased to provide a ‘top up’ to government parental leave benefits for eligible employees on maternity/parental leave.  In addition, Queen’s provides partial reimbursement for eligible daycare expenses for employees with dependent children in daycare. Details are set out in the Queen’s-QUFA Collective Agreement. For more information on employee benefits, see Queen’s Human Resources.

Additional information about Queen’s University can be found on the Faculty Recruitment and Support website. The University is situated on the traditional territories of the Haudenosaunee and Anishinaabe, in historic Kingston on the shores of Lake Ontario. Kingston’s residents enjoy an outstanding quality of life with a wide range of cultural, recreational, and creative opportunities. Visit Inclusive Queen’s for information on equity, diversity and inclusion resources and initiatives.

The University invites applications from all qualified individuals. Queen’s is strongly committed to employment equity, diversity and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous/Aboriginal people, women, persons with disabilities, and 2SLGBTQ+ persons.  All qualified candidates are encouraged to apply; however, in accordance with Canadian immigration requirements, Canadian citizens and permanent residents of Canada will be given priority.

To comply with federal laws, the University is obliged to gather statistical information as to how many applicants for each job vacancy are Canadian citizens / permanent residents of Canada. Applicants need not identify their country of origin or citizenship; however, all applications must include one of the following statements: “I am a Canadian citizen / permanent resident of Canada”, OR “I am not a Canadian citizen / permanent resident of Canada”. Applications that do not include this information will be deemed incomplete.

In addition, the impact of certain circumstances that may legitimately affect a nominee’s record of research achievement will be given careful consideration when assessing the nominee’s research productivity. Candidates are encouraged to provide any relevant information about their experience and/or career interruptions.

A complete application consists of:

  • a cover letter (including one of the two statements regarding Canadian citizenship / permanent resident status specified above);
  • a current Curriculum Vitae (including a list of publications);
  • a statement of teaching interests and experience (including teaching outlines and evaluations if available); and
  • the names and contact information of three referees.

Applications should be submitted on or before April 30, 2021.  Applicants are encouraged to send all documents in their application packages electronically as a single PDF, Attn: Chair of Faculty Search Committee at cssearch2021@cs.queensu.ca.

Applicants should arrange for ***THREE*** letters of recommendation to be sent directly by their three selected referees to the Chair of Faculty Search Committee at refletter2021@cs.queensu.ca by the closing date of April 30, 2021. Only candidates selected for interviews will be contacted.

The University will provide support throughout the recruitment processes to applicants with disabilities, including accommodations that take into account an applicant’s accessibility needs. If you require accommodation during the interview process, please contact Tom Bradshaw in the School of Computing at bradshaw@cs.queensu.ca.

Academic staff at Queen’s University are governed by a Collective Agreement between the University and the Queen’s University Faculty Association (QUFA).

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Biomedical Informatics Teaching Positions Available for the School of Computing – Spring/Summer 2021

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 19, 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 2020/2021 Spring Term

This spring term period is from May 1, 2021 to June 30, 2021.

Classes will be in session from May 10, 2021 to June 21, 2021.

Applications will be received until March 19, 2021.



BMIF-801* Programming Skills and Tools for Processing Biomedical Data
The objective of this course is to provide graduating health science students hands-on training in computer programming languages and tools to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research.
Prerequisite: none


BMIF-802* Biomedical Data Analysis
The objective of this course is to provide graduating health science students hands-on training in the analysis of biomedical datasets to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research.
Prerequisite: none

 



Academic Year 2020/2021 Summer Term

This summer term period is from July 1, 2021 to August 31, 2021.

Classes will be in session from July 5, 2021 to August 13, 2021.

Applications will be received until March 19, 2021.



BMIF-803* Data Mining and Applications
The objective of this course is to provide graduating health science students with hands-on training in data mining to familiarize them with the principles and practice of cutting edge technologies for bioinformatics used in biomedical and molecular sciences research. Prerequisite: none


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Teaching Assistant Positions available for 2020-2021 in the School of Computing

The Teaching Assistant Positions are available in the School of Computing for the 2020-2021 academic year.

To apply for a TA position:

  1. Go to https://auth.caslab.queensu.ca/ta/cisc. You will be prompted by the Queen’s sign-on portal for your netid and password.
  2. After logging on, provide your name and email to the system.
  3. Next, go to the “TA applications” tab at the top of the page, select “Provide background”, and provide your background information. Then click “Submit” at the bottom of the page.
  4. Finally, and only after providing your background and clicking “Submit” on that page, go to the “TA applications” tab, select “Apply”, and indicate the courses to which you are applying. Then click “Submit”.

The system will tell you when your application is complete.

Incomplete applications will not be considered.

You must reside in Canada to be hired as a TA.

For more information please contact:

Debby Robertson
Graduate Program Assistant
School of Computing
Queen’s University

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Postdoctoral Fellowship Opportunities

There are no positions currently available in the School of Computing.

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