Under the direction of Dr. Katz, the fellow will collaborate with Dr Milios and Dr Bruijn in applying the evolving NLP techniques based on deep language models (such as Bidirectional Encoder Representations from Transformers) to the analysis of electronic medical record free text clinical notes and imaging reports and their linkage to the structured patient data held in the Repository.
This is a full-time position for a two-year period, contingent on satisfactory performance. The Fellow will receive a salary of $55,000 - $58,000 (commensurate with qualifications) with full staff benefits, university office space, use of appropriate computer services, and access to university libraries.
Qualifications : -PhD in Computer science, computer engineering or a related field. -Experience with and interest in pursuing a career in natural language processing, text mining or machine learning for text using deep language models.
Outstanding and demonstrated skills writing for peer reviewed publication. -Excellent verbal communication skills.-Ability to work with a high degree of independence and initiative.
Ability to make and adhere to self-imposed timelines.Additional Information : Interested candidates should submit their application (a cover letter, curriculum vitae, two recent publications, and the contact information of three academic references) to : Sophie Buternowsky : All applicants are thanked in advance;
only those selected for further consideration will receive a response. Review of applications will begin on Nov 30th and will continue until this position is filled.
The position will begin on April 1 or as soon as possible thereafter. The University of Manitoba is strongly committed to equity and diversity within its community and especially welcomes applications from women, racialized persons, Indigenous peoples, persons with disabilities, persons of all sexual orientations and genders, and others who may contribute to the further diversification of ideas.
All qualified candidates are encouraged to apply; however Canadian citizens and permanent residents will be given priority.