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The Department of Biological Science in the Faculty of Science invites applications for a Research Associate – Biological Data Science. This Full-time Fixed Term position is for approximately 2 years (based on length of grant funding), with the possibility of extension.
The Precision Infection Management (PIM) program is a collaborative research effort at the University of Calgary that began in 2017, which involves research teams based at the University of Calgary, Alberta Precision Laboratories, MIT-Broad Institute and Harvard University School of Public Health. In 2018, The PIM has received major boost through Genome Canada Large Scale Applied Research Project program. PIM occupies new state of the art computational and experimental laboratories in the U of C Biological Sciences building.
The Biological Data Science group consists of core faculties (Dr. Ian Lewis and Dr. Sergei Noskov in the Department of Biological Sciences) joined by diverse and talented team of staff, students and post docs, as well as many collaborators on campus and internationally. We work on various projects where clinical data, metabolomics and genomics information obtained for clinical isolates may improve precision medicine and prescription practices for the infection diseases. This includes research related to combatting antibiotic-resistance emerging nationally and globally. PIM initiative is supported by research funding from the University of Calgary, Province of Alberta, Genome Canada and Canadian Institutes for Health Research. We are seeking new colleagues to join our team as post-doctoral research associates.
The Research Associate will report to Drs. Ian Lewis and Sergei Noskov, Principal Investigators of PIM initiative. The incumbent will also be involved into software and database development activities with Dr. Ian Lewis, Alberta Innovate Translational Health Chair – Metabolomics. Regular collaboration with other team members in the context of clinical and biological data is expected and encouraged. The research associate will conduct their own software development for metabolomics and proteomics analysis, and computational experiments as well as provide support and mentoring to other team members (e.g., grad students, undergraduate project and summer students, visitors, etc) who need to set up similar experiments. Applicants who have recently completed a PhD (<3 years) can also join the University of Calgary through the post-doctoral scholars program (http://www.ucalgary.ca/research/postdoc).
Summary of Key Responsibilities (job functions include but are not limited to):
Technical
- Development of data processing workflow for sample processing, metabolomics, proteomics, genomics, and clinical data
- Development of computational tools for monitoring quality control in the sample preparation and analysis workflow
- Development of statistical models for integrating clinical data with biochemical datasets and identifying clinically significant biochemical traits of microbes
- Extension of machine-learning and statistical modelling to metabolomics dataset
- Maintenance and participation in the PIM portal
- Development of kinetic models for description of bacterial metabolic networks
- Data organization, visualization and analytics for biological data acquired from analytical biochemistry techniques such as GC-MS, NMR and genomics
Reporting and Publications
- Publication of results in peer-review journals is anticipated
- Maintain a clear and well-documented log of all data
- Meet with supervisor regularly (e.g. monthly meetings, as well as interactions on a day to day basis) to provide update on status of experimental results
- Presentation of results to the PIM initiative research groups in team meetings (e.g. once a month) and if necessary, to industry sponsors and Research Oversight Committee (ROC)
- Project representation at international conferences
Safety and Environment
- Understanding of standard operating procedures of the equipment used in the experimental protocols
- Maintain a clean and safe laboratory work area
Other
- Manage time effectively to complete project work and contribute yearly research updates to program sponsors
- Perform other duties, as assigned by the Research Supervisor
- Contribute on a daily basis towards a positive working environment within a large and diverse team of colleagues working in the PIM group
Qualifications / Requirements
- PhD in area of Computational Biophysics/Chemistry/Biology
- At least 5 years of experience in programming with Python and Linux shell
- At least 5 years of experience with large scale HPC computing as well as code optimization with specific applications in the mixed computational environments of super-computer clusters
- At least 5 years of experience in Data Analytics of biological data sets
- At least 3 years of experience in applications of Machine Learning techniques (Scikit-Learn, PyTorch, Tensorflow, etc.) to biochemical problems modelling proven by research articles in peer reviewed scientific journals
- At least 2 years of experience with large datasets of clinical, biochemical, and biological data such as biological data formats (PDB, FASTA, MOL2, SDF).
- At least 2 years of experience processing mass-spectrometry data (MS1, MS2, MS3) from proteomics and metabolomics experiments (RAW, mzML, mzXML, MGF) from isobaric labeling experiments (TMT11), quantitative proteomics and liquid chromatography-mass spectrometry (LCMS) as well as knowledge of MS-software packages in Linux environments (e.g. MaxQuant)
- At least one year of experience in the analysis and development of Quality Control pipelines from instruments to persistent storage with examples of applications to proteomics and metabolomics data collection
- At least 2 years of experience with cheminformatics toolkits (e.g. RDKit)
- At least 2 years of experience with data analysis in the area of bacterial metabolomics, genomics and proteomics
- Fundamental background in linear algebra, statistics and analytical mathematics (e.g. through university courses taken in related disciplines)
- At least one year of experience in development of statistical models for biomarkers discovery
- Experience with software engineering and maintenance of code bases, development, testing, documentation, deployment and maintenance of software products for Linux, Windows and MacOS (e.g. GitHub repository)
- At least 2 years of experience with web development frameworks in Python (Django, Flask) and knowledge of HTML, CSS and experience with dashboard development (Dash).
- Experience with containerization technology (Docker, Singularity) is an asset
- Experience with databases (SQL, Postgres) and Big Data technology (Hive, Hadoop, Spark) is an asset
- Knowledge of WHMIS
- Ability to multi-task and deal with repetitive tasks
- Strong organizational and time management skills with proven experience in managing multi-PI initiatives involving experimental and computational tasks
- Excellent verbal and written communication skills with proven experience in scientific publishing in peer reviewed scientific journals or grant writing
- Must be comfortable working in a diverse research team and have good interpersonal skill
- Ability and willingness to teach and mentor early career scientists (e.g. upper level undergraduate and graduate students)
Application Deadline: May 4, 2020
For more information and to apply for the position (Job ID# 20383), please CLICK HERE.
We would like to thank all applicants in advance for submitting their resumes. Please note, only those candidates chosen to continue on through the selection process will be contacted.
