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Land Acknowledgement The University of Guelph resides on the treaty lands and territory of the Mississaugas of the Credit. We recognize this gathering place where we work and learn is home to many past, present, and future First Nations, Inuit, and Métis peoples. Our acknowledgement of the land is our declaration of our collective responsibility to this place and its peoples’ histories, rights, and presence.
General Information (Six PDF Positions Available) This post-doctoral position will be part of the Food from Thought initiative funded through a Canada First Research Excellence Award: https://foodfromthought.ca/. Contributing to this large endeavour to improve food security and sustainability, our goal is to generate bioinformatics strategies for the prediction of biodiversity and ecosystem services from diverse data types, such as -omics data, digital photographs, and/or environmental data. Data analysis has begun to catch up with the pace of data generation, and in these times where understanding and mitigating the effects of climate change and feeding a growing human population is of utmost importance, we need to turn our sights on connecting different sources of data and extracting actionable meaning from them. The successful applicants will utilize existing and new biological and environmental datasets, along with additional external data, with the goal of predicting ecosystem services, ecosystem health status, and biodiversity metrics using approaches such as statistical learning, machine learning, and network analysis. This may include such important factors as pollination, invasive species resistance, pest control, trophic interactions, water quality, and others. Successful applicants will be part of a cohort of six postdoctoral scholars focused on bioinformatics and ecosystem services, who will work together with a multidisciplinary team of Principal Investigators, students, staff, industry members, and communities.
What We Offer • The opportunity to engage in creative and impactful research relevant for sustainability and food security • The opportunity to collaborate with researchers in a variety of fields, including computer science, statistics, ecology, evolutionary biology, and genomics • Guidance to build valuable skills and to be well prepared for diverse future careers (skills include scientific research; collaboration; communication with diverse stakeholders; technical skills relating to coding, data analysis, graphics, code review, and publishing of bioinformatics tools) • Access to unique data sets and participation in collaborative partnerships with academics, industry, and governmental agencies • Regular, inclusive, and supportive mentorship from multiple PIs with diverse expertise to support your research, career, and impact/outreach goals • Participation in a collaborative working group of PDFs, workshops, and conferences • Monetary support for professional development, workshop participation, and conference attendance (up to $5000) as well as open-access publishing ($3000)
Specific Information (PDF in Statistical Modelling Environmental Effects Monitoring) We are seeking candidates interested in developing statistical methods and predictive models for environmental effects monitoring. Statistical learning and ecological network modelling will be developed to predict ecosystem services, ecosystem health status, and biodiversity directly using raw metagenomic data (DNA sequence reads from whole communities of organisms, including insects and microbes). Specific applications may include study of ecosystem health in freshwaters impacted by industrial effluents or agricultural activities. This work is important for developing efficient methods to leverage high-throughput data to perform biomonitoring and to support decision making. Successful applicants will also be committed to respectful collaboration and communication, including with industry and academic collaborators as well as community groups. Anticipated deliverables from the research include: one or more scientific publication(s), well-commented code that is made publicly available by the end of the project, and a user manual (and GUI, if suitable) for any bioinformatics tools created such that the predictive models are user friendly and can respond to future data availability. The successful PDFs will also be expected to participate in a PDF Working Group (which may include collegial discussion, collaboration, and/or reciprocal code reviews prior to publication), in the annual Knowledge Mobilization Working Group Meetings, as well as in at least one relevant scientific or industry conference. The successful applicant may also play a role in co-mentoring an undergraduate or graduate student. The selected candidate will be based in the research group of Dr. R. Ayesha Ali (Professor of Statistics & Director of Master of Data Science Program) and will also benefit from working closely with a co-advisor with complementary expertise in bioinformatics or integrative biology as well as other collaborators.
Required Qualifications & Attributes • Must hold a PhD in statistics, bioinformatics, genomics, applied mathematics or a related discipline • Published at least one first-authored paper in a peer-reviewed journal • Experience with coding in at least one computer language (intermediate to advanced level required; skills must include: data formatting and filtering, data exploration and quality checking, graphics, data analysis; prior experience in usage of high-performance computing resources an asset; prior experience in software development and code testing an asset) • Experience with at least one of: statistical analysis, analysis of DNA sequencing data, machine learning, and/or statistical learning • Commitment to transparent and reproducible science (evidence of this commitment could include prior publication of code and/or a thorough methods section in your prior publication(s)) • Commitment to respectful interactions with others and to equity, diversity & inclusion (evidence of this attribute could include: prior or planned mentorship activities or collaborations; participation in relevant committees or working groups; your personal communication practices, etc.)
Application Requirements A completed application will consist of: • Cover letter describing your interest in the position and highlighting how you meet the required qualifications and attributes • Curriculum vitae (including education history, experience and skills, publications, conference presentations, outreach or leadership activities, interests) • Names and contact information for three referees (You may feel to include academic advisors, collaborators, and/or an individual you have mentored) • PDF reprint of 1-3 publications (should be first author of at least one work published or in press; preprints are welcome among the selected submissions) Please combine all of the above components into a single PDF and email to: Dr. R. Ayesha Ali, Professor: firstname.lastname@example.org
Length of Appointment & Salary The PDF position is available for two years. Goal setting will be completed collaboratively early in the position, and progression will be discussed through regular meetings and reviewed at the one-year mark. The salary range is $47,000-$52,000 Canadian dollars annually, plus 17.2% value in benefits. The selected candidate will also benefit through access to $5,000 in travel funds for workshops and conferences and $3,000 to publish in open-access venues.
Deadline Review of applications will commence on December 6, 2022 and proceed until the position is filled. The start date will be as soon as possible thereafter (subject to discussion with the successful applicant).
Equity, Diversity & Inclusion We strongly support diversity in science, and applicants from under-represented racial, cultural, gender-identity, physical ability, and/or neurological spectra are particularly encouraged to apply. Applications can be received immediately; however, evaluation of the applications will not commence until December 6, 2022 in order to allow for a diverse applicant pool to be evaluated.
To apply for this job please visit www.mathjobs.org.