Oregon State University (OSU), University of Oregon (UO), and Portland State University (PSU) are establishing an interdisciplinary cross-institutional team of data science analysts/trainers to conduct data integration, multi-modal data analytics, and machine learning research and training. There will be four analyst/trainers each with expertise in one or more of these three areas and collectively spanning all three areas; two at OSU, one at UO and one at PSU. These positions will collaborate with, assist, and train scientists of all levels in data-intensive research in the life, health, earth, physical and marine sciences.
Two positions will be located in the Center for Genome Research and Biocomputing at Oregon State University and one each in the Data Science Initiative at the University of Oregon and in the Center for Life in Extreme Environments at Portland State University.
Appointees will jointly serve researchers at the three institutions, as well as smaller institutions across Oregon and southern Washington. They will nucleate and integrate a wider team of data analytics professionals to support each other, connect to relevant expertise, and promote cross-institutional collaboration. They will provide consulting (project planning; proposal assistance), data analysis, teach training courses, and arrange colloquia to inform and instruct faculty, staff and students. This position will contribute to advancing the diversity, equity and inclusion goals of each university. Appointees are required to collaborate in a collegial and inclusive fashion with university staff and clients in the execution of all job functions.
40% Data Analytics training
• Implement multi-campus training program consisting of short workshops and classes (3 days to 5 weeks) in topics in data analytics, including:
o Data fundamentals: a foundational course that covers good data and software practices, including data privacy and cyber security.
o Data integration: transforming data held in different sources making it more valuable and presenting users with a unified view. Discovery, access, preparation, aggregation, curation, transformation, semantic harmonization, and sharing.
o Multimodal data analytics: analytics across heterogenous, high dimensional data sets, using structured data. Data aggregation, model building and uncertainty quantification.
o Machine Learning: approaches such as differential programming, deep learning, or artificial intelligence.
• Develop and implement new workshops and classes in other related topics, as desired by the three institutions and research community served by the positions
• Incorporate distance learning methodologies, webinars, online materials, or other cutting-edge educational solutions where needed, to provide a high quality of service for learners
• One-on-one training activities specific to individual learner needs
• Organize cross-institutional user group meetings and other community-based efforts
50% Collaborative research
• Plan and execute research proposals and funded projects with collaborators in the areas of data integration, multimodal data analytics, and machine learning. Analyze data and prepare reports from this research for publications and research proposals. Present research at conferences.
10% Community outreach
• Engage regional institutions in the community of practice, including smaller institutions and underserved communities of users, through summer research opportunities, training of faculty and service providers, collaborative curricular development, and online participation in community activities.
This position will interact with a wide variety of faculty, staff, and students representing a broad range of expertise and cultural backgrounds. This position will support each university’s mission of equity, inclusion, diversity and social justice by respecting, welcoming and supporting the diverse perspectives of our clientele. We are currently engaged in work bringing STEM learning to underrepresented groups, so candidates with experience and interests in outreach and engagement with underserved communities are warmly encouraged to apply.
How to Apply
For full consideration please apply by July 9, 2021. Applications must include the following materials:
• A Current resume or CV detailing experience
• A cover letter clearly describing how you meet the minimum qualifications, preferred qualifications, and your commitment to diversity and inclusion
• Names and contact information for 3 references
Oregon State University
Job Posting Number: P04081UF
Application Link: jobs.oregonstate.edu/postings/96571
• M.S. or higher degree in data analytics, statistics, bioinformatics, or computer science, or related field (at time of hire).
• Minimum of one term experience as a teaching assistant in data analytics, statistics, computational biology or computer science, or equivalent experience with formalized delivery of training in an industrial, academic or other setting.
• Demonstrable research or teaching experience in data integration, multi-modal data analytics, or machine learning
• Demonstrated problem-solving skills, independence, high motivation, and excellent communication skills, both orally and written.
• Strong organizational and time management skills.
• Ph.D. in bioinformatics, computational biology, computer science, engineering, mathematics, statistics, or related field.
• Research experience in life, health, earth or marine sciences
• Teaching experience in life, health, earth or marine sciences
• Experience with distance learning technologies and methodologies.
• Experience in a Linux or Unix environment.
• Experience as an industry or academic consultant in data analytics, statistics, bioinformatics, or computer science.
• Undergraduate degree or diploma in computer science, statistics or equivalent.
• Proficiency in one or more programming languages (R, Python, CUDA, Java, or similar)
• Experience working in a service position.
• Experience in outreach and engagement with underserved communities
• A demonstrable commitment to promoting and enhancing diversity
Application Link: jobs.oregonstate.edu/postings/96571