Teaching Positions Available for the School of Computing – Spring/Summer 2018

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 22, 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

Applicants must have (or very close to finishing) a PhD in computer science or equivalent discipline.

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/

 



CISC 897
Taught May 8 to May 25, weekdays 9:00am to 12:00pm (noon), except May 21 (Victoria Day)

Provides incoming students with basic research and working skills, facilitating a smoother transition to graduate studies and research. The course spans multiple elements including time management, writing and presentation skills, and general considerations for experiment design and planning.


 

BMIF 801
Taught May 28 to June 15, weekdays from 9:00am to 12:00pm (noon)

Provides students with hands-on training in computer programming languages, software tools and algorithms used in biomedical research. Topics will include an introduction to programming in R and MATLAB, pre-processing and management of biomedical datasets, identification of outliers, workflow for quality control assessments, and basics of cloud computing. Examples of real biomedical datasets will be provided to illustrate the application of programming tools.


 

BMIF 802
Taught June 18 to July 6, weekdays from 9:00am to 12:00pm (noon)

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.


 

Applications will be received until March 22, 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 – 2 Tenure-track Faculty Positions

The School of Computing in the Faculty of Arts and Science at Queen’s University invites applications for two Tenure-track faculty positions at the rank of Assistant Professor with specialization in Data Analytics, Machine Learning, Big Data and related areas. The preferred starting date is July 1, 2018.

Successful candidates must have a PhD or equivalent degree in Computer Science, Software Engineering or a related discipline completed at the start date of the appointment. They are expected to play a major role in the delivery of the Data Analytics graduate and undergraduate programs at the School of Computing. The successful candidates are expected to be part of a Queen’s-wide Data Sciences cluster involving the Faculty of Arts and Science, Faculty of Applied Science and Engineering, Faculty of Health Sciences and the Smith School of Business. They will also be involved in the planned Queen’s Data Analytics Institute with excellent opportunities for funding and collaboration.

The main criteria for selection are academic and teaching excellence. The successful candidates will provide evidence of high quality scholarly output that demonstrates a record for independent research leading to peer-assessed publications in one of the foundational areas of Computer Science. A commitment to secure external research funding, as well as strong potential for outstanding teaching contributions at both the undergraduate and graduate levels, and ongoing dedication to academic and pedagogical excellence in support of the School’s programs are requirements for these positions. Ability to work in collaborative multidisciplinary settings, course development and student supervision are required. 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.

Queen’s University is one of Canada’s leading research-intensive universities with a global reputation and is a recognized leader in Canadian higher education. The School of Computing has 22 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 historic campus is located in the heart of the vibrant Kingston community in the Thousand Islands region of South Eastern Ontario. Queen’s is positioned centrally with respect to three major metropolitan areas: Toronto, Montreal, and Ottawa. 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. We encourage 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,
  • the names and contact information of three referees.

The deadline for applications is February 15, 2018. However, the selection process will continue until the position is filled. Applicants are encouraged to send all documents in their application packages electronically as a single PDF, Attn: Chair of Faculty Search Committee at CSsearch@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
CANADA K7L 3N6

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 February 15, 2018.

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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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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