School of Computing – Tier 2 Canada Research Chair in Biomedical Computing and Informatics

The School of Computing, Faculty of Arts and Science and the Department of Biomedical and Molecular Sciences, Faculty of Health Sciences at Queen’s University invite applications for a joint tenure-track faculty position as a Tier 2 Canada Research Chair in Biomedical Computing and Informatics, with a preferred starting date of July 1, 2019. The appointment will be at the rank of Assistant or Associate Professor, depending upon the level of experience of the successful candidate. This position is subject to final budgetary approval by the University.

Candidates must hold a PhD degree. The successful candidate will have a background in computer science, though consideration will be given to those with equivalent training and demonstrable abilities and focus in bioinformatics, computational biology, and/or biomedical data science. The ideal candidate will demonstrate that they are an outstanding scientist and educator with passion, energy, and a strong vision for innovative research in biomedical computing. The preferred candidate must demonstrate comprehensive expertise in one or more of the following areas of biomedical computing specializations: Bioinformatics, Biomedical Data Analytics, Physiological Modeling and Analytics, Medical Imaging, Feature Extraction and Classification and Applications of Machine Learning on Biomedical Data. Evidence of clinical health research collaborations or strong potential/ability to attract clinical health collaborative initiatives is an asset.

The preferred candidate must have a distinguished record of accomplishment in discovery and innovative research, and an ability to collaborate with colleagues in the School of Computing and Department of Biomedical and Molecular Sciences, as well as with other scientists and clinical researchers at Queen’s University. The successful candidate is expected to be part of a Queen’s-wide Data Sciences cluster involving the Faculty of Arts and Science, the Faculty of Engineering and Applied Science, the Faculty of Health Sciences and the Smith School of Business. The candidate will also be involved in the planned Queen’s Data Analytics Institute with excellent opportunities for funding and collaboration.

As part of the submitted application, the successful candidate will: (i) provide evidence of high-quality scholarly output that demonstrates potential for independent research leading to peer-assessed publications and an externally-funded world-class research program; and (ii) demonstrate strong potential to make outstanding teaching contributions at both the undergraduate and graduate levels and an ongoing commitment to academic and pedagogical excellence in support of the Departments’ programs. Applicants will be expected to provide evidence of an ability to work collaboratively in an interdisciplinary and student-centered environment. The successful applicant will be strongly encouraged to apply for external funding to support the supervision and training of students and other highly qualified personnel.

Queen’s University is host to numerous research centres and research groups, housing scientists with research interests that will complement the successful applicant. These include the Human Mobility Research Centre (HMRC Queen’s Chronic Pain Clinic at Hotel-Dieu Hospital); the Cardiac, Circulatory and Respiratory Research Group and Queen’s Cardiopulmonary Unit (QCPU); and the Queen’s Cancer Research Institute (QCRI). These groups and units maintain extensive regional, national and global research collaborations. Additionally, the Centre for Advanced Computing (CAC) at Queen’s delivers a world-class high-performance computing environment and storage resources.

Canada Research Chairs are established as part of a national strategy to foster research excellence. The candidate must meet the requirements for the position of Tier 2 Chair as defined by the CRC program. Tier 2 Canada Research Chairs are intended for exceptional emerging scholars who are less than 10 years from their highest degree at the time of nomination. Applicants who are more than 10 years from their highest degree due to career breaks may have their eligibility for a Tier 2 CRC assessed through the program’s Tier 2 justification process. For full program information, including further details on eligibility criteria, please consult the CRC website: www.chairs-chaires.gc.ca/.

The University invites applications from all qualified individuals. Queen’s is committed to diversity and inclusion and has an employment equity program that meets the goals of the Canada Research Chairs program and the requirements of our collective agreement with the Faculty Association. Until such time as we have met our equity targets (http://queensu.ca/vpr/prizes-awards-chairs/canada-research-chairs-program-crcp), preference will be given to members of the Four Designated Groups under the Canada Research Chairs program: women, Indigenous/Aboriginal peoples, persons with disabilities and racialized persons/visible minorities. All applicants will be invited to self-identify once they have applied; those who wish to be considered under our employment equity provisions are required to self-identify. Self-identification information will be held in confidence by the Equity Office and one member of the selection committee. 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 about 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 comprehensive list of publications, awards, and grants received);
  • a statement of current and prospective research interests and experience;
  • a statement of teaching experience and interests together with a teaching portfolio (including teaching outlines and evaluations if available);
  • Applicants should arrange for ***THREE*** letters of recommendation to be sent directly to Chair of Faculty Search Committee at hiring.letters@cs.queensu.ca by the closing date of ***August 1, 2018***. At least one of referees must be at arm’s length.

The deadline for applications is August 1, 2018. Applications will continue to be reviewed until a suitable candidate is found. Applicants are asked to send all documents in their application packages electronically as PDFs to Dr. Hossam Hassanein, Director of the School of Computing, Queen’s University, Kingston, Ontario, K7L 3N6 at BMC.CRC2@cs.queensu.ca.

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.

Appointments are subject to review and final approval by the Provost. Only nominees external to Queen’s University will be considered. (Please note that, for the purposes of this competition, Queen’s Term Adjuncts and Adjunct-1s will be considered as external nominees.)

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Teaching Positions Available for the School of Computing – 2018-19 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 June 8, 2018. 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 2018/2019 Fall Term

This fall term period is from September 1, 2018 to December 31, 2018.

Classes will be in session from September 6, 2018 to November 30, 2018.

Applications will be received until June 8, 2018.



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.
NOTE Sufficient preparation for CISC 121/3.0. Students without programming experience should take CISC 110/3.0 (or CISC 101/3.0) before CISC 121/3.0. With permission of the instructor, students with programming experience may take this course concurrently with CISC 121/3.0.
LEARNING HOURS 120 (36L;84P)
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 or CISC at the 200-level or above.


CISC 221/3.0 Computer Architecture
The descriptive levels of computer architecture. Instruction-set architectures. Assembly Language. Data representation. Support for operating-system management and high-level languages. Input/output and interrupts. Designing for performance. Digital Logic.
LEARNING HOURS 120 (12L;24G;84P)
RECOMMENDATION CISC 220/3.0.
PREREQUISITE Level 2 or above and C- in CISC 124/3.0.


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)
PREREQUISITE Level 2 and [(C- in CISC 101/3.0 or CISC 110/3.0 or CISC 121/3.0)] or permission of the Instructor.
EQUIVALENCY CISC P82/3.0.


CISC 432/3.0 Advanced Data Management Systems
Storage and representation of “big data”, which are large, complex, structured or unstructured data sets. Provenance, curation, integration, indexing and querying of data.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Registration in a School of Computing Plan and C- in (CISC 235/3.0 and CISC 332/3.0).


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 486/3.0 Game Development
An introduction to ‘engines’ used in networked 3-dimensional games. Topics include game-engine architecture and components providing 3-dimensional rendering, physics simulation, sound, artificial intelligence and networking services.
LEARNING HOURS 120 (36L;15G;69P)
PREREQUISITE Registration in a School of Computing Plan and C- in [CISC 226/3.0 and (CISC 322/3.0 or CISC 326/3.0) and CISC 324/3.0 and (MATH 110/6.0 or MATH 111/6.0 or MATH 112/3.0)].


CISC490 Topics in Computer Science: Cyber Security
Overview of computer security, privacy and trust, types of security, confidentiality, integrity, and availability. User authentication and access control. Software security, secure software development. Operating system security. Malicious software. Cryptography and network security, intrusion detection systems. Security management.
PREREQUISITE CISC 324/3.0


CISC P81/3.0 Computers: Applications and Implications
Computers are changing our lives; this is a course for any student interested in learning about computing. It surveys many fields of computing science, presents case studies of fascinating examples of computers in use in diverse areas, from searching the world-wide web to medicine, and discusses the possibilities, limitations, and risks of computers.
LEARNING HOURS 120 (36L;12G;72P)


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 2018/2019 Winter Term

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

Classes will be in session from January 7, 2019 to April 5, 2019.

Applications will be received until June 8, 2018.




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 220/3.0 System-Level Programming
Basic concepts of Unix-like systems. Shells and scripting. System-level programming in the C language. Software development tools and techniques.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Level 2 or above and C- in CISC 121/3.0.
COREQUISITE CISC 124/3.0.


CISC 226/3.0 Game Design
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)
PREREQUISITE Level 2 or above and C- in CISC 124/3.0.


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 453/3.0 Topics in Artificial Intelligence
Investigation of selected areas of artificial intelligence research. Possible topics include natural language understanding, computational perception, planning, learning, and neurocomputing.
LEARNING HOURS 120 (36L;84P)
PREREQUISITE Registration in a School of Computing Plan and C- in CISC 352/3.0.


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).


CISC-897* 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


CISC P81/3.0 Computers: Applications and Implications
Computers are changing our lives; this is a course for any student interested in learning about computing. It surveys many fields of computing science, presents case studies of fascinating examples of computers in use in diverse areas, from searching the world-wide web to medicine, and discusses the possibilities, limitations, and risks of computers.
LEARNING HOURS 120 (36L;12G;72P)


 

Applications will be received until June 8, 2018.

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Post-Doctoral Fellowship in Text Data Analytics at Queen’s School of Computing (BAM Lab)

Posting Date: Mar 5, 2018 (revised – higher salary and international applicants will be considered)
Job Title: Post-Doctoral Fellow, School of Computing, Queen’s University
Funded by: IBM and CIMVHR (Canadian Institute of Military and Veteran Health Research)
Department: School of Computing, Queen’s University
Collaborators: University of Manitoba, Western University
Project Title: Defining Post Traumatic Stress Disorder (PTSD) in Primary Care Electronic Medical Record (EMR) Data to Explore Prevalence, Patient Characteristics and Primary Care Experiences of Veterans, Families of Military Service Members and the General Population
Research Areas: Natural Language Processing (NLP), text mining, machine learning, knowledge representation and management, medical decision support system
Supervision: Dr. Farhana Zulkernine and academic collaborators (primarily Dr. Alexander Singer, University of Manitoba)
Remuneration: $50,000 CDN per year (including all benefits)
Start Date: May 1st, 2018
Duration: 2 years
Application Deadline: Until hired
Application Procedure: Apply by email by sending the application package to
farhana@cs.queensu.ca.

Qualifications: We seek a candidate with proven expertise in text data mining, natural language processing (NLP), deep learning/machine learning, knowledge management using big data storage systems
and knowledge sharing using cloud services. The work will focus on using NLP and text mining techniques to extract terms that are representative of PTSD diagnosis from doctors’ chart notes stored in the EMR systems. The data must be anonymized and analyzed to extract indicators of possible development or progression towards developing PTSD and diagnosis of PTSD in different sectors such as veteran population, their families and general public to understand and evaluate quality of primary care for patients with PTSD. The extracted and analyzed data must be stored to enable knowledge translation and sharing with the research community.

A PhD in Computer Science or a comparable qualification is required. The successful candidate must have a good research record with publications in relevant international conferences and journals, text analytics, and machine learning. The candidate is expected to have an active role in various collaboration efforts with other universities and industry, both at the national and international level. Good communication and project management skills and willingness to work in a team are essential. Additional information about Dr. Zulkernine’s research and the project can be found at http://cs.queensu.ca/~farhana/.

The position is for two years and is funded by IBM and CIMVHR (Canadian Institute for Military and Veteran Health Research). The candidate will be working in the Big Data Analytics and Management laboratory (BAM Lab) at the School of Computing, Queen’s University but will be closely collaborating with Dr. Alex Singer at the University of Manitoba and other collaborators involved in this project. Periodic reports must be presented about the status and progression of the work. The candidate will also be expected to supervise other graduate and undergraduate students on relevant project and will have an opportunity to have joint publications and gather experiences in academic jobs.

The School of Computing is one of the premier computing departments in Canada with about 30 faculty members and close to 150 graduate students. Kingston is Canada’s first capital and is centrally located between Toronto, Ottawa, and Montreal. The United Nations rates Canada as one of the best countries in the world to live. The project will provide a unique opportunity to the candidate to work with multiple experts on an interdisciplinary research which will contribute to Canada’s health care system and allow exploration of cutting edge tools and techniques in text data analytics, knowledge management, and machine learning.

Please send an application package to farhana@cs.queensu.ca containing:

  1.  A cover letter explaining experiences relevant to the project.
  2. A curriculum vitae with detailed information regarding your academic degree,
    research projects and publications.
  3. Names and email addresses of three referees.
  4. Sample publications (1-2 recent publications).

***Canadian citizen/immigrant/permanent resident will be given priority.

EMPLOYMENT EQUITY: The University invites applications from all qualified candidates. 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 persons of any sexual orientation or gender identity.

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School of Computing Teaching Opportunities

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

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Postdoctoral Fellowship Opportunities

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

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