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加拿大英属哥伦比亚大学医学数据分析博士后职位
文章来源:知识人网整理       更新时间:2021年04月06日

加拿大英属哥伦比亚大学医学数据分析博士后职位

英属哥伦比亚大学(UBC)

Summary of the position

•Term: 1 year full-time position with possible extension for future year(s).

• Salary: Commensurate with qualifications and experience

• Desired start date: May 1, 2021 (negotiable)

• Location: Digital Emergency Medicine, UBC, Vancouver General Hospital campus

• Academic supervisor: Dr. Kendall Ho, UBC Department of Emergency Medicine

• Contract type: Temporary

Note: This position is limited to individuals currently permitted to work in Canada.

Summary of the project

The project will focus on the research and development of machine learning algorithms and deep learning methods when applied to digital lung auscultation data and other relevant data. The developed pipelines will be validated using real patient data and rigorous usability test protocols and will be deployed to provide decision support to frontline healthcare providers, once validated.

The research fellow will take a prominent leadership role in refining and conducting the research plan as presented below. The position is highly suitable for those pursuing a research career in advanced data analytics in academic or industry, particularly in the life sciences, but also in other application domains such as electrical engineering and human-interface design.

The research fellow will be co-supervised by an interdisciplinary team led by Dr. Kendall Ho (UBC Department of Emergency Medicine) and Dr. Roger Tam (UBC School of Biomedical Engineering). It will offer a great opportunity for the fellow to collaborate closely with data scientists, health researchers, and clinicians to generate impactful and meaningful outcomes.

Required Qualifications and Experience

Candidates should hold a Ph.D. in Computing Science, Biomedical Engineering, Electrical Engineering, or other related fields. Ideal candidates should have experience working with medical data and analyzing data to predict health states. Qualified individuals will have the following experience and skills:

•Demonstrated competence in the use of computer science, data science, machine learning, and deep learning methods to analyze medical data;

•Practical knowledge in generative models, semi-supervised learning, and interpretable artificial intelligence;

•Experience developing cross-validated models and conducting reproducible experiments;

•Strong familiarity with deep learning toolkits such as Tensorflow and Torch;

•Ability to write structured and annotated code, scripting, run unit tests and debugging;

•Ability to lead the authorship of manuscripts for submission to both clinical and technical journals;

•Ability to effectively use statistical software at an advanced level;

•Ability to work effectively both independently and collaboratively in a team environment;

•Ability to interact productively and professionally with a wide range of internal and external collaborators as well as junior trainees;

•Strong organizational, time management, and project management skills.

Additional desired qualifications

•Experience working with acoustic, wearable sensor data, and/or medical imaging data.

•Experience managing studies with (ongoing) acquisition of patient data.

•Background and knowledge in medical device design, manufacturing and certifications.

•Familiarity with multiple programming languages and tools such as Java, C++, Python, R, MATLAB, and SAS (Statistical Analysis Software).

Research Plan

The project is aimed to produce two algorithmic prototypes that will be developed using in-house and open-source datasets of digital lung auscultation data:

•Primary: annotate sound files in terms of disease states (e.g. normal vs. pneumonia).

•Secondary: score severity rating of the disease captured by each sound file.

The research fellow will execute the following research plan:

I. Literature review: conduct thorough literature review to acquire the clinical and technical background needed to achieve the research outcomes; identify the strengths and limitations of the available in-house and open-source datasets; perform a detailed assessment on how each dataset could be leveraged for each research outcome listed above.

II. Model development: propose and implement a method for each research outcome and perform rigorous experimentation during the model development phase, which includes the proper set-up of reproducible cross-validation experiments, evaluation of model parameters using various parameters, and documentation of preliminary research results.

III. Usability testing: patient data will be collected in controlled settings to facilitate the testing/validation of the developed algorithm(s). Other members of the study team will facilitate access and approval to work within these settings while the research fellow will take leadership in validating the developed pipelines and produce formal reports to document the test results.

To Apply

Please email Mr. Michael Lim (program manager) at michael.l [at] ubc.ca your application as a single PDF with subject “RADAR: postdoc fellow position [your full name]”.

Your application should include a cover letter, your curriculum vitae, and full contact information of up to three professional references.

This posting is for the UBC Vancouver campus in British Columbia, Canada.

Please refer to reference number NC-54973 during correspondence about this position. Please visit the researcher profile of the supervisor for this position to learn more about their research.

Equity and diversity are essential to academic excellence. An open and diverse community fosters the inclusion of voices that have been underrepresented or discouraged. We encourage applications from members of groups that have been marginalized on any grounds enumerated under the B.C. Human Rights Code, including sex, sexual orientation, gender identity or expression, racialization, disability, political belief, religion, marital or family status, age, and/or status as a First Nation, Metis, Inuit, or Indigenous person.

About UBC

The University of British Columbia is a global centre for research and teaching, consistently ranked among the top 20 public universities in the world. Since 1915, UBC’s entrepreneurial spirit has embraced innovation and challenged the status quo. UBC encourages its students, staff and faculty to challenge convention, lead discovery and explore new ways of learning. At UBC, bold thinking is given a place to develop into ideas that can change the world.

Postdoctoral Fellows at UBC Vancouver

UBC is home to over 900 postdocs spanning all faculties and units across two campuses and a variety of affiliated hospitals, research centres, and sites, providing unparalleled opportunities to learn, discover and contribute in one’s own way. UBC’s Postdoctoral Fellows Office (PDFO) is committed to supporting the lives and career aspirations of our Postdocs, with the goal of enriching their experience at UBC and preparing them for the future. In addition to providing support and advocacy for all postdocs, the PDFO is dedicated to providing professional development opportunities that foster the development of soft skills needed in today’s professional environments, helping them secure future careers in their chosen fields.

About UBC’s Faculty of Applied Science

The Faculty of Applied Science comprises a unique constellation of disciplines – including the Schools of Architecture and Landscape Architecture, Community and Regional Planning and Nursing, as well as all engineering activities at both the Vancouver and Okanagan campuses. Our work and the professional disciplines we represent span the entire human-centred built environment and innovation at all scales – from nanoscale electronic devices that power communications to the design of entire cities.

There has never been a more urgent time for our professions – as planners, architects, nurses and engineers – to come together to build upon our existing strengths and ambitions to ensure a thriving society, to make real impact locally and globally.

With a community of over 300 full-time faculty members and more than 8,600 students across our undergraduate and graduate programs, we shape the leaders and professions that shape the world.

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