Research Assistant Tech 3

3 weeks ago

Vancouver, British Columbia, Canada UBC Full time
Staff - Non UnionJob CategoryNon Union Technicians and Research AssistantsJob ProfileNon Union Salaried - Research Assistant /Technician 3Job TitleResearch Assistant Tech 3 - Lange labDepartmentLange Laboratory | Department of Pathology and Laboratory Medicine | Faculty of MedicineCompensation Range$4, $5,228.81 CAD MonthlyPosting End DateJune 5, 2024

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

Job End Date

Jun 16, 2025

This position is located within a health-care facility. Therefore, this positions requires successful verification of full vaccination against Covid-19 provided prior to the start date, as required by the provincial health mandate.

The anticipated start date for this position is June 17, 2024. The term is for one year with the possibility of extension.

In your application please include (1) a cover letter, and (2) a CV or resume.

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

The Lange Lab is a creative, forward looking and nimble team of scientists that analyzes and decodes the human proteome to find new treatment opportunities for children with cancer. We embrace tough challenges and take pride in pushing fundamental research all the way to improving patient's care - today. In our latest research published in Nature Communications we used new statistical and data analysis strategies to establish a strong rational for starting personalized precision diagnostics immediately at diagnosis. Together with our partners we have informed the treatment of patients and paved the way to bring precision oncology to the next level.

We are seeking a passionate bioinformatician who joins us to build and grow proteomics guided precision oncology with us. If you are a self-motivated multitasker who enjoys wrangling data, coding analysis and reporting pipelines and making intuitive yes scientifically accurate representations of complex data - we would like to hear from you

We offer a high degree of flexibility and opportunities for ongoing professional development. This is an exciting opportunity to start your career in biomedical data analysis and be part of national projects to re-think pediatric cancer research and care from the ground up

Your main role will be to support and advance the groups analysis of mass spectrometric proteomics data. You will analyze complex proteomics data and take pride in their effective visualization. You will analysis and machine learning pipelines in R and Python and develop and maintain data repository and sharing platforms.

We Offer:

· A dynamic and diverse work environment.

· An attractive compensation package including health benefits

· The opportunity participate in building a new data analysis and reporting platform for proteomics research at the BC Children's Hospital Research Institute.

· The opportunity to work with and learn from world experts in proteomics and genomics at UBC, BC Cancer Research Centre and the BCCHRI.

· The opportunity to work with multidisciplinary experts in the Canadian Pediatric Cancer Consortium (CPCC) and Precision Oncology for Young People (PROFYLE) to improve precision oncology for children by integrating genomic, proteomic, drug sensitivity, phenotypic and clinical information.

· The opportunity to conduct research and develop new methods.

· Plentiful opportunities to advance your skills and take on new roles.

Organizational Status
You will report directly to Dr. Philipp Lange, Canada Research Chair in Translational Proteomics of Pediatric Malignancies.

Work Performed

  • Assist with contributing to the development of data repositories and analysis pipelines to streamline analysis and interpretation and work with leading data scientists across the country to advance date sharing and interoperability
  • Assist with developing strategies to better integrate molecular (proteomics, genomic, metabolomic) and phenotypic (clinical, immunophenotype, drug perturbation, ...) data using classical and machine learning approaches
  • Assist in the analysis of proteomic data from patient biopsies to identify potentially targetable perturbations
  • Engage with team members and collaborators to make key contributions to data analysis & visualization of proteomics data
  • Contribute to manuscript and grant preparation and present your work at scientific meetings
  • Contribute to training lab members in statistics and data analysis and introduce new methodologies to the lab
  • Other duties as required

Consequence of Error/Judgement
Errors may result in the misinterpretation or misrepresentation of research data. This may result in the failure of a funded project and put in jeopardy any future funding and the international reputation of the Laboratory and the Institute. It may also result in misdirecting future research locally and internationally.

Supervision Received
Works under minimal supervision, receiving specific instructions only on unusual problems or when receiving new projects outlines from the principal investigator.

Supervision Given
Train students and junior lab staff; has input on staff/co-op student selection and performance evaluation.

Minimum Qualifications
Completion of a relevant technical program or a university degree in a relevant discipline and a minimum three years of related experience or an equivalent combination of education and experience.

- Willingness to respect diverse perspectives, including perspectives in conflict with one's own

Demonstrates a commitment to enhancing one's own awareness, knowledge, and skills related to equity, diversity, and inclusion

Preferred Qualifications

  • B.Sc. or M.Sc. graduate in Bioinformatics, biostatistics or other appropriate discipline, preferred
  • Demonstrated ability to work independently and communicate effectively with faculty, staff, trainees, and collaborators.
  • Advanced knowledge and demonstrated experience in R and/or Python for data analysis and machine learning
  • Advanced knowledge and demonstrated experience in data visualization
  • Advanced knowledge and demonstrated experience in statistics
  • Proven troubleshooting and code debugging skills.
  • Skills in proteomics or transcriptomics data analysis, databases, protein function prediction, machine learning for genomics & proteomics and generative models, considered an asset.
  • Strong organizational skills and ability to work in a team-oriented environment.
  • Good English verbal and written communication skills.

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