Job Description

Staff - Non Union

Job Category Non Union Technicians and Research Assistants

Job Profile Non Union Salaried - Research Assistant /Technician 4

Job Title Computational Technician

Department Shakiba Laboratory | School of Biomedical Engineering | Faculty of Medicine

Compensation Range $5,068.91 - $5,946.08 CAD Monthly

Posting End Date February 12, 2024

Note: Applications will be accepted until 11:59 PM on the day prior to the Posting End Date above.

Job End Date Aug 11, 2024

At UBC, we believe that attracting and sustaining a diverse workforce is key to the successful pursuit of excellence in research, innovation, and learning for all faculty, staff and students. Our commitment to employment equity helps achieve inclusion and fairness, brings rich diversity to UBC as a workplace, and creates the necessary conditions for a rewarding career.

Job Summary
We are seeking a computational biologist with experience in both computational modeling and high-throughput sequencing data analysis to join the research groups of Dr. Nika Shakiba in Vancouver, Canada. The primary responsibility of the candidate will be, based on available scRNA data, to develop a computational model describing the self-organization process of precursor cells into Blood Vessel Organoids capillary networks. The successful candidate will recognize the critical genes and pathways involved in arterio-venous patterning and identify the mechanisms behind spontaneous symmetry breaking events in the growth of BVOs. Other responsibilities may include support data analysis of trainees in the group and provide technical documentations for grant reports and other reporting needs. The selected candidate will work with a multidisciplinary team of other bioinformatics scientists and stem-cell biologists.

Organizational Status
The position will report directly to the Principal Investigator. Contract is for 6 months and is renewable pending on performance and funding.

Work Performed

- Use technically advanced procedures and conducts complex analysis of organoids scRNA and spatial transcriptomic data

- Research and infer regulatory networks (GRN) to improve our understanding of cell fate in organoid growth

- Develop a computational model to simulate organoid growth in-silico, with emphasis on arterio-venous patterning

- Design experiments, analyze data, and interpret results

- Participate in scientific discussions and presentations

Consequence of Error/Judgement

Work is expected to be at a high level of accuracy with excellent attention to detail. Errors in judgement could affect and delay operations of the BRC, the School, individual faculty members, students and other stakeholders and overall impact their reputation.

Exercises a considerable amount of judgment, responsibility, and initiative in determining work procedures and methods, and coordinating the work of the unit.

Supervision Received
Works under minimum supervision, receiving specific instructions only on unusual problems or on matters which depart significantly from established policy and procedure.

Supervision Given
May have supervisory responsibilities for a small group of employees at lower classifications and may have input into staff selection and performance evaluation.

Minimum Qualifications
Completion of a university degree in a relevant discipline or technical program and a minimum four years of related experience or an equivalent combination of education and experience. Some positions may require a graduate degree.

- Willingness to respect diverse perspectives, including perspectives in conflict with one\xe2\x80\x99s own

- Demonstrates a commitment to enhancing one\xe2\x80\x99s own awareness, knowledge, and skills related to equity, diversity, and inclusion.

Preferred Qualifications

- MSc or PhD in computer science, bioinformatics, computational biology, or relevant experience or certification.

- Documented prior experience analyzing high-throughput sequencing data and scRNA.

- Documented prior experience in inferring gene regulatory networks.

- Documented prior experience in developing stochastic or agent-based models.

- Strong analytical skills and a solid foundation in statistical analysis.

- Demonstrated ability to work in a team environment (references required).

- Strong proficiencies in Python and R.

- Willing to work on a variety of bioinformatics and data science-related projects.

- Excellent oral and written communication skills and ability to organize, analyze, and communicate scientific data.

- Proficiency in documentation of code and applications.

- Independent and takes initiative in multitasking and multi-disciplinary environments.

University of British Columbia