Tenure-Track Position in Cybersecurity at Queen’s School of Computing

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for a Tenure-track faculty position at the rank of Assistant Professor with specialization in Cybersecurity with a preferred starting date of July 1, 2020.  In the case of an exceptional candidate, a tenured appointment at the rank of Associate Professor may be considered.

Candidates must have a PhD or equivalent degree in Computer Science, Engineering or a related discipline completed at the start date of the appointment. The main criteria for selection are academic and teaching excellence. The successful candidate will provide evidence of high quality scholarly output that demonstrates potential for independent research leading to peer assessed publications and the securing of external research funding, as well as strong potential for outstanding teaching contributions at both the undergraduate and graduate levels, and an ongoing commitment to academic and pedagogical excellence in support of the School’s programs. Candidates must provide evidence of an ability to work collaboratively in an interdisciplinary and student-centred environment. The successful candidate will be required to make substantive contributions through service to the School, the Faculty, the University, and/or the broader community. Salary will be commensurate with qualifications and experience.

Strongly qualified applicants from all areas of cybersecurity are encouraged to apply. The following areas of specialization are of particular interest: cryptography, privacy, computer and network forensics, and other emerging areas in application security including but not limited to blockchain, Internet of Things, mobile, data and cloud security..

The successful candidate is expected to play a major role in the delivery of graduate and undergraduate programs at the School of Computing. The successful candidate is also required to design and teach graduate and undergraduate courses on the aforementioned topics, secure external funding and establish a research stream on cybersecurity.

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 School of Computing has 29 full-time and 20 cross-appointed faculty, over 500 undergraduate students, and over 140 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.

The University invites applications from all qualified individuals. Queen’s is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, Aboriginal peoples, persons with disabilities, and LGBTQ 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 in the previous paragraph);
  • a current Curriculum Vitae (including a list of publications);
  • a statement of research interests;
  • a statement of teaching interests and experience (including teaching outlines and evaluations if available); and,
  • three letters of reference to be sent directly to 2020RefLetterSec@cs.queensu.ca.

The deadline for applications is October 31, 2019. Applicants are encouraged to send all documents in their application packages electronically as a single PDF, Attn: Chair of Faculty Search Committee at 2020CSSearchSec@cs.queensu.ca; alternatively, hard copy applications may be submitted to:

Faculty Search Committee Chair
The School of Computing
557 Goodwin Hall
Queen’s University
Kingston, Ontario K7L 3N6
CANADA

The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes 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), which is posted at http://queensu.ca/facultyrelations/faculty-librarians-and-archivists/collective-agreement and at http://www.qufa.ca.

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Tenure-Track Position in Human-Computer Interaction at Queen’s School of Computing

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for a Tenure-track faculty position at the rank of Assistant Professor with specialization in Human-Computer Interaction with a preferred starting date of July 1, 2020.  In the instance that an exceptional candidate is identified, a tenured appointment at the rank of Associate Professor may be considered. Candidates with specialization in all areas of Human-Computer Interaction are encouraged to apply, including: interaction design, accessibility, playful interaction, user interface engineering, and novel interaction techniques including augmented and virtual reality, wearables, and bodily interaction.

Candidates must have a PhD or equivalent degree in Computer Science, Engineering or a related discipline completed at the start date of the appointment. The main criteria for selection are academic and teaching excellence. The successful candidate will provide evidence of high quality scholarly output that demonstrates potential for independent research leading to peer assessed publications and the securing of external research funding, as well as strong potential for outstanding teaching contributions at both the undergraduate and graduate levels, and an ongoing commitment to academic and pedagogical excellence in support of the School’s programs. The successful candidate is expected to play a major role in the delivery of graduate and undergraduate programs at the School of Computing. Candidates must provide evidence of an ability to work collaboratively in an interdisciplinary and student-centred environment. The successful candidate will be required to make substantive contributions through service to the School, the Faculty, the University, and/or the broader community. Salary will be commensurate with qualifications and experience.

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 School of Computing has 29 full-time and 20 cross-appointed faculty, over 500 undergraduate students, and over 140 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.

The University invites applications from all qualified individuals. Queen’s is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, Aboriginal peoples, persons with disabilities, and LGBTQ 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 in the previous paragraph);
  • a current Curriculum Vitae (including a list of publications);
  • a statement of research interests;
  • a statement of teaching interests and experience (including teaching outlines and evaluations if available); and,
  • three letters of reference to be sent directly to 2020RefLetterHCI@cs.queensu.ca.

The deadline for applications is October 31, 2019. Applicants are encouraged to send all documents in their application packages electronically as a single PDF, Attn: Chair of Faculty Search Committee at 2020CSSearchHCI@cs.queensu.ca; alternatively, hard copy applications may be submitted to:

Faculty Search Committee Chair
The School of Computing
557 Goodwin Hall
Queen’s University
Kingston, Ontario K7L 3N6
CANADA

The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes 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), which is posted at http://queensu.ca/facultyrelations/faculty-librarians-and-archivists/collective-agreement and at http://www.qufa.ca.

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Tenure-Track Position in Software Engineering at Queen’s School of Computing

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for a Tenure-track faculty position at the rank of Assistant or Associate Professor in Software Engineering with a preferred starting date of July 1, 2020.  In the case of an exceptional candidate, a tenured appointment at the rank of Associate Professor would be considered. All areas of Software Engineering are welcome. The following areas are of particular interest: Software Engineering with and for AI and Machine Learning, DevOps, Performance Engineering, Program Analysis, Testing and Software Quality.

The successful candidate must have a PhD or equivalent degree in Computer Science, Software Engineering or a related discipline completed at the start date of the appointment. The successful candidate is expected to play a major role in the delivery of graduate and undergraduate programs at the School of Computing. The main criteria for selection are academic and teaching excellence. The successful candidate will provide evidence of high quality scholarly output that demonstrates potential for independent research leading to peer-assessed publications and the securing of external research funding, as well as strong potential for outstanding teaching contributions at both the undergraduate and graduate levels, and an ongoing commitment to academic and pedagogical excellence in support of the School’s programs. Candidates should demonstrate an ability to work collaboratively in an interdisciplinary and student-centred environment. The successful candidate will be required to make substantive contributions through service to the School, the Faculty, the University, and/or the broader community. Excellent interpersonal skills and exceptional oral and written communication proficiency are required. Salary will be commensurate with qualifications and experience.  This position is subject to final budgetary approval by the University.

Queen’s University is one of Canada’s leading research-intensive universities. We are focused on being the quality leader in Canadian higher education and are dedicated to promoting research and scholarship of national and international distinction. The School of Computing has 29 full-time and 20 cross-appointed faculty, over 500 undergraduate students, and over 140 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.

Queen’s University is one of the oldest universities in Canada and has a global reputation for teaching and research excellence. The main campus is located within walking distance to the vibrant downtown area. Kingston is on the shore of Lake Ontario and near the Thousand Islands region of south-eastern Ontario. Kingston and the surrounding region boast a wide range of recreational opportunities and a rich arts and cultural community. In addition to Queen’s University, Kingston is home to St. Lawrence College and the Royal Military College of Canada.

Additional information about Queen’s University, which may be of interest to prospective faculty members, can be found at http://www.queensu.ca/facultyrecruitment.

The University invites applications from all qualified individuals. Queen’s is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, Aboriginal peoples, persons with disabilities, and LGBTQ 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.

A complete application consists of:

  • a cover letter (including one of the two statements regarding Canadian citizenship / permanent resident status specified in the previous paragraph);
  • a current Curriculum Vitae (including a list of publications);
  • a statement of research interests;
  • a statement of teaching interests and experience (including teaching outlines and evaluations if available); and,
  • three letters of reference to be sent directly to 2020RefLetterSE@cs.queensu.ca.

The deadline for applications is October 31, 2019.

Applicants are encouraged to send all documents in their application packages electronically as a single PDF, Attn: Chair of Faculty Search Committee at 2020CSsearchSE@cs.queensu.ca; alternatively, hard copy applications may be submitted to:

Faculty Search Committee Chair
The School of Computing
557 Goodwin Hall
Queen’s University
Kingston, Ontario K7L 3N6
CANADA

The University will provide support in its recruitment processes to applicants with disabilities, including accommodation that takes 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.

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Tenure-Track Teaching Focused Position in Computing, Queen’s University, July 2020

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for a teaching focused tenure-track faculty position at the rank of Assistant or Associate Professor. The preferred start date for the appointment is May 1, 2020. Salary will be commensurate with qualifications and experience.

Candidates should 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.  Experience in securing external research funding would be an asset.

The main criteria for selection are: (i) a genuine, demonstrated commitment to academic and teaching excellence in a post-secondary computing education environment (such as adjunct/sessional lecturing experience) and; (ii) a capacity for research in a field related to computer science or software engineering. The successful candidate will be expected to demonstrate outstanding teaching contributions at both the undergraduate and graduate levels corresponding to approximately 70% of the position time. 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.

Qualified candidates must provide evidence of high-quality scholarly output that demonstrates potential for independent research, including supervision of undergraduate and graduate students. Additionally, 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, including the Biomedical Informatics graduate diploma and master’s program; and
  • provide effective service contributions to the School, the Faculty of Arts and Science, the University and the broader community.

The University invites applications from all qualified individuals. Queen’s is committed to employment equity and diversity in the workplace and welcomes applications from women, visible minorities, Indigenous peoples, persons with disabilities, and LGBTQ 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.

Queen’s University is one of Canada’s leading research-intensive universities. We are focused on being the quality leader in Canadian higher education and are dedicated to promoting research and scholarship of national and international distinction. The School of Computing has 29 full-time and 20 cross-appointed faculty, over 500 undergraduate students, and over 140 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.

Queen’s University is one of the oldest universities in Canada and has a global reputation for teaching and research excellence. The main campus is located within walking distance to the vibrant downtown area. Kingston is on the shore of Lake Ontario and near the Thousand Islands region of south-eastern Ontario. Kingston and the surrounding region boast a wide range of recreational opportunities and a rich arts and cultural community. In addition to Queen’s University, Kingston is home to St. Lawrence College and the Royal Military College of Canada.

Additional information about Queen’s University, which may be of interest to prospective faculty members, can be found at http://www.queensu.ca/facultyrecruitment.

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);
  • a statement of research interests; and
  • the names and contact information of three referees.

Applications should be submitted on or before September 30, 2019.  Applicants are encouraged to send all documents in their application package electronically as a single PDF, Attn: Chair of Faculty Search Committee at 2020CSSearchTeaching@cs.queensu.ca, although hard copy applications may be submitted to:

Faculty Search Committee Chair
The School of Computing
557 Goodwin Hall
Queen’s University
Kingston, Ontario K7L 3N6
CANADA

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 2020RefLetterTeaching@cs.queensu.ca by the closing date of September 30, 2019. Only candidates selected for interviews will be contacted.

The University will provide support throughout the recruitment process 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), which is posted at http://queensu.ca/facultyrelations/faculty-librarians-and-archivists/collective-agreement and at http://www.qufa.ca.

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Teaching Assistant Positions available for 2019-2020 in the School of Computing

The Teaching Assistant Positions are available in the School of Computing for the 2019-2020 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.

Deadline is August 1, 2019. Incomplete applications will not be considered.

For more information please contact:

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

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Teaching Positions Available for the School of Computing – 2019-20 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 March 15, 2019. 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 2019/2020 Spring Term

This fall term period is from May 1, 2019 to June 30, 2019.

Classes will be in session from May 6, 2019 to June 17, 2019.

Applications will be received until March 15, 2019.



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)
ONE-WAY EXCLUSION May not be taken with or after CISC 352/3.0; PSYC 200/6.0.


BMIF-802/3.0 Biomedical Data Analysis
Provides students with hands-on training in analysis of biomedical datasets. Topics  will include feature extraction and classification, pattern recognition, supervised and unsupervised learning, and basic concepts of biostatistics as applied to the analysis of biomedical data. Examples of real biomedical datasets will be provided to demonstrate various methodologies for data analysis. Prerequisites for this course include BMIF 801 as well as admission in the Graduate Diploma (GDip [BI]) or permission of the Course Instructor.

 



Academic Year 2019/2020 Summer Term

This fall term period is from July 1, 2019 to August 31, 2019.

Classes will be in session from July 2, 2019 to August 12, 2019.

Applications will be received until March 15, 2019.



CISC 121/3.0 Introduction to Computing Science I
Introduction to design and analysis of algorithms. Recursion, backtracking, and exits. Sequences, linked lists and references. Binary search trees. Elementary searching and sorting. Assertions and loop invariants. Order-of-magnitude complexity. Numerical computation. Documentation, 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); see Introductory Courses in Departmental Notes.
COREQUISITE CISC 102/3.0 or MATH 110/6.0 or MATH 111/6.0 or MATH 112/3.0 or MATH 120/6.0 or MATH 121/6.0 or MATH 123/3.0 or MATH 124/3.0 or MATH 126/6.0 or APSC 171/3.0 or APSC 172/3.0 or APSC 174/3.0 or COMM 161/3.0 or COMM 162/3.0.


CISC 124/3.0 Introduction to Computing Science II
Introduction to object-oriented design, architecture, and programming. Use of packages, class libraries, and interfaces. Encapsulation and representational abstraction. Inheritance. Polymorphic programming. Exception handling. Iterators. Introduction to a class design notation. Applications in various areas.
LEARNING HOURS 120 (36L;24Lb;60P)
PREREQUISITE C- in CISC 121/3.0.
COREQUISITE CISC 102/3.0 or MATH 110/6.0 or MATH 111/6.0 or MATH 112/3.0 or MATH 120/6.0 or MATH 121/6.0 or MATH 123/3.0 or MATH 124/3.0 or MATH 126/6.0 or APSC 171/3.0 or APSC 172/3.0 or APSC 174/3.0 or COMM 161/3.0 or COMM 162/3.0.


CISC-897/3.0 Research Methods in Computer Science     
This course provides an introduction to the primary and secondary sources of information in the computing science literature. The course includes work aimed at improving research skills. Students are required to submit and present a paper on a topic that relates to their research.
Prerequisite: none

 



Academic Year 2019/2020 Fall Term

This fall term period is from September 1, 2019 to December 31, 2019.

Classes will be in session from September 5, 2019 to November 29, 2019.

Applications will be received until March 15, 2019.



CISC 101/3.0 Elements of Computing Science
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.
LEARNING HOURS 120 (36L;24Lb;60P)


CISC 181/3.0 Digital Societies
This introductory course provides a broad overview and ethical implications of technological topics and trends in the digital world such as the Internet of Things (IoT), Social Networks, Security and Privacy, Data Analytics, and Artificial Intelligence (AI). No programming experience is required.
LEARNING HOURS 120 (36L; 84P)


CISC 322/3.0 Software Architecture
Abstractions and patterns of interactions and relationships among modules. Design recovery; relationship of architecture to requirements and testing.LEARNING HOURS 120 (36L;24T;36G;24P)
PREREQUISITE Registration in a School of Computing Plan and C- in (CISC 203/3.0 and CISC 204/3.0 and CISC 223/3.0 and CISC 235/3.0).
EXCLUSION No more than 3.0 units from CISC 322/3.0 and CISC 326/3.0.


CISC 330/3.0Computer-Integrated Surgery
Concepts of computer-integrated surgery systems and underlying techniques such as medical-image computing, robotics, and virtual reality, learned through real-life applications and problems. Techniques learned in class will be applied in a hands-on surgery session where students perform minimally invasive surgery with virtual-reality navigation tools.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Registration in a School of Computing Plan and C- in (CISC 121/3.0 and CISC 271/3.0).
EXCLUSION No more than 3.0 units from CISC 330/3.0; COMP 329/3.0; COMP 230/3.0.
EQUIVALENCY COMP 230/3.0.


CISC 435/3.0 Computer Communications and Networks
Fundamental concepts in the design and implementation of computer communication networks, protocols, and applications. Overview of network architectures; applications; network programming interfaces (e.g., sockets); transport; congestion; routing and data link protocols; addressing; local area networks; wireless networks, mobility management; security.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Registration in a School of Computing Plan and C- in CISC 324/3.0.


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;84P)
PREREQUISITE C- in (CISC 333/3.0 or CISC 351/3.0).


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- in (COGS 100/3.0 or PSYC 100/6.0).
EXCLUSION No more than 6.0 units from COGS 200/6.0; COGS 201/3.0; PSYC 220/6.0.

 



Academic Year 2019/2020 Winter Term

This fall term period is from January 1, 2019 to April 30, 2019.

Classes will be in session from January 6, 2019 to April 3, 2019.

Applications will be received until March 15, 2019.



CISC 181/3.0 Digital Societies
This introductory course provides a broad overview and ethical implications of technological topics and trends in the digital world such as the Internet of Things (IoT), Social Networks, Security and Privacy, Data Analytics, and Artificial Intelligence (AI). No programming experience is required.
LEARNING HOURS 120 (36L; 84P)


CISC 121/3.0Introduction to Computing Science I
Introduction to design and analysis of algorithms. Recursion, backtracking, and exits. Sequences, linked lists and references. Binary search trees. Elementary searching and sorting. Assertions and loop invariants. Order-of-magnitude complexity. Numerical computation. Documentation, 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); see Introductory Courses in Departmental Notes.
COREQUISITE CISC 102/3.0 or MATH 110/6.0 or MATH 111/6.0 or MATH 112/3.0 or MATH 120/6.0 or MATH 121/6.0 or MATH 123/3.0 or MATH 124/3.0 or MATH 126/6.0 or APSC 171/3.0 or APSC 172/3.0 or APSC 174/3.0 or COMM 161/3.0 or COMM 162/3.0.


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.
LEARNING HOURS 120 (36L;36Lb;48P)
EXCLUSION No more than 3.0 units from APSC 142/3.0; APSC 143/3.0; CISC 101/3.0; CISC 110/3.0; CISC 151/3.0.
ONE-WAY EXCLUSION May not be taken with or after CISC 121/3.0; CISC; SOFT at the 200-level and above.


CISC 181/3.0 Digital Societies
This introductory course provides a broad overview and ethical implications of technological topics and trends in the digital world such as the Internet of Things (IoT), Social Networks, Security and Privacy, Data Analytics, and Artificial Intelligence (AI). No programming experience is required.
LEARNING HOURS 120 (36L; 84P)


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- in CISC 124/3.0 and C- in (CISC 102/3.0 or MATH 110/6.0).
COREQUISITE CISC 204/3.0.


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)


CISC 324/3.0 Operating Systems
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)
PREREQUISITE Registration in a School of Computing Plan and C- in (CISC 221/3.0 and CISC 235/3.0).


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- in (CISC 121/3.0 and CISC 221/3.0 and CISC 223/3.0).


COCA 201/3.0 Introduction to Computing and the Creative Arts
A multidisciplinary studio-oriented overview of computer-based applications in Art, Music, Drama and Film. History of human-computer interaction. Critical and philosophical issues. Animation. Virtual reality. Computer-aided design. Computer games. Enrolment is limited.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Level 2 or above and (C- in 6.0 units in ARTF or ARTH or DRAM or FILM or MUSC at the 100-level.
COREQUISITE CISC 101/3.0 or CISC 110/3.0 or CISC 121/3.0 or CISC 151 or permission of the School of Computing.


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