Computational Data Scientist Artificial Intelligence

University of Idaho

United States

February 21, 2022


Position Details Posting Number SP003205P

Position Title Computational Data Scientist Artificial Intelligence Location Moscow Division/College University Research (Div) Department Institute for Interdisciplinary Data Sciences FLSA Status Overtime Exempt Employee Category Exempt Pay Range $85,000 per year or higher depending on experience Type of Appointment Fiscal Year FTE


Full Time/Part Time Full Time Position Overview

The Computational Data Scientist (Artificial Intelligence (AI)/Machine Learning focus) will be a part of a new initiative in Computational One Health at the University of Idaho. Computational One Health is a widely adopted framework that views human, wildlife, and livestock health as an integrated system. We seek to add four new hires to our Computational One Health team: A Computational Data Scientist (Machine Learning / Artificial Intelligence (AI) focus—this position), a Computational Scientist, a Data Scientist, and a Bioinformatics Data Scientist. This position will complement and strengthen our Computational One Health team by providing expertise in AI and machine learning applications. This expertise is critical for the analysis and forecasting components of One Health and will rely on the data streams provided by the Bioinformatics Data Scientist and Data Scientist positions in this cluster.

The Computational Data Scientist will develop mathematical and machine learning approaches to forecast the risk of animal-borne infectious diseases and the effectiveness of potential interventions. This position will also collaborate with faculty and researchers within the Institute for Interdisciplinary Data Sciences (IIDS) Research Computing and Data Services (RCDS) core facility, as well as faculty and researchers across campus. Duties of this position will include assisting to develop and lead research projects as a Principal Investigator (PI) or Co-PI including writing grant proposals, writing code, managing projects, compiling, analyzing, and maintaining associated data, and publishing papers in peer-reviewed journals. This position will lead research projects and collaborate with staff, students, and postdocs. They will employ strong communication skills in a highly collaborative team to accomplish shared goals.

Unit Overview

The Institute for Interdisciplinary Data Sciences (IIDS) is a research institute within the Office of Research and Economic Development (ORED) at the University of Idaho. The mission of IIDS is to empower researchers to fully harness the potential of the data revolution by provisioning and administering critical University research infrastructure related to genomics, bioinformatics, research computing, and data science. IIDS houses three service units including Research Computing and Data Services (RCDS), the Genomics and Bioinformatics Resources Core (GBRC), and the Initiative for Bioinformatics and Evolutionary Studies (IBEST) and is a vibrant home for interdisciplinary research for student, postdoc, and faculty participants. IIDS participants can access expertise and infrastructure, support for proposal development and grants management, and training and professional development activities.

Funding This position is contingent upon the continuation of work and/or funding. A visa sponsorship is available for the position listed in this vacancy. Uncertain Internal Posting?

Position Responsibilities

Key Accountability Conducting and supporting collaborative team science in Computational One Health by:

Job Duties

  • Providing all aspects of design, analysis, programming, testing, and implementation of new and existing artificial intelligence and machine learning applications.
  • Independently implementing and troubleshooting software pipelines that incorporate artificial intelligence and machine learning approaches.
  • Effectively communicating (verbally and in writing) complex data analysis, machine learning techniques and results to collaborators and trainees.
  • Communicating research findings through publications in peer-reviewed journals, online repositories that document code used in simulations or analyses (e.g., GitHub), and through presentations.
  • Mentoring and facilitating undergraduate and graduate research.
  • Collaboratively applying machine learning and other AI approaches to new and existing databases and models developed by other Computational One Health team members.
  • Engaging (as PI or Co-PI) with researchers on research plan development.
  • Developing (as PI or Co-PI) research proposals to federal, state, and private agencies and foundations.
  • Key Accountability Contribute to research teams across campus by:

    Job Duties

  • Collaborating with other researchers to resolve complex computational problems and recommend and/or implement appropriate solutions.
  • Collaborating with laboratory and field colleagues to facilitate, optimize, and troubleshoot data generation and analysis.
  • Contributing to a collaborative and congenial team environment with other research groups across campus such as the Idaho Center for Agriculture, Food, and the Environment (CAFE) and the Institute for Modeling Collaboration and Innovation (IMCI), as well as activities such as seminars, workshops, retreats, core meetings, and other associated meetings.
  • Collaborating with the RCDS team to identify priority technical initiatives that support the institution's strategic plan as it applies to research, research computing, and data management.
  • Helping guide improvements to campus resources and computing infrastructure to increase institutional capacity to leverage AI and Machine Learning methods.
  • Innovating, designing, developing, deploying, and maintaining modular software systems and related technologies to support interactive data management, visualization, and dissemination for the UI research community.
  • Collaborating with university staff and internal/external partners to develop and integrate new services, tools, and products into the core IIDS IT architecture.
  • Customizing and adapting applications and databases as needed to meet evolving partner and user-community requirements.
  • Consulting with potential scientific collaborators on a technical level to match their scientific needs with possible technical solutions. (i.e., propose core research computing architectures or specific applications where possible and provide other solutions if core architecture is not an option).
  • Serving as the point-of-contact for assigned funded projects and as a support representative to manage and resolve technical issues encountered by collaborators and other users (e.g., provide technical support for collaborators by researching, developing, and implementing innovative web/mobile based solutions that satisfy their needs).
  • Providing and coordinating technical support as needed via email, phone, Slack, Zoom, and other methods.
  • Key Accountability Continued professional development by:

    Job Duties

  • Maintaining current knowledge of computational science, especially in the areas of artificial intelligence and machine learning.
  • Reviewing and keeping abreast of current scientific literature.
  • Actively participating in relevant professional societies and organizations.
  • Providing professional service to the broader research community including serving as an independent reviewer for journal manuscripts and funding proposals.
  • Disseminating results by publication in peer-reviewed journals.
  • Developing scientific collaborations and relationships (e.g., attending meetings and research conferences, seminars, and working with committees).
  • Required Experience

    At least 3 years demonstrated experience related to the domain of this position:

  • Writing research software with computer languages commonly used in scientific programming (e.g., Python, R, MATLAB, Mathematica, C/C++).
  • Experience using common AI/Machine Learning frameworks such as TensorFlow, PyTorch, scikit-learn, Caret, nnet, or similar.
  • Experience optimizing AI/Machine Learning algorithms, including the use of distributed computing and GPU platforms.
  • Communicating with peers and coworkers on complex research and technology issues and presenting technical content in diverse large group and individual settings with people who have varying degrees of technical experience as demonstrated in application materials.
  • Working both independently and within a team managing multiple complex projects with competing deadlines.
  • Employing machine learning and artificial intelligence to conduct data- intensive scientific research.
  • Evaluating machine learning results, including the use of confusion matrices, ROC curves and AUC, learning curves, or similar metrics.
  • Feature extraction from tabular and image data.
  • Working with large data sets, especially in their preparation for computationally intensive analyses or rendering them interoperable with additional data sets.
  • Required Education

  • PhD in Computer Science, Computational Biology, Bioinformatics, Systems Biology, Biostatistics, Mathematics, Statistics, Data Science, or a related discipline.
  • Required Licensures, Certifications or other Additional Preferred

  • Ability to effectively use machine learning and artificial intelligence as demonstrated by authorship on peer-reviewed scientific publications.
  • Knowledge of zoonotic pathogens and epidemiology.
  • Experience working in a UNIX/Linux command line environment.
  • Experience working with graduate and undergraduate researchers.
  • Serving as PI, Co-PI, or senior personnel on extramural grants.
  • Successfully developed and applied novel neural network architectures to specific problem domains.
  • Experience with feature importance estimation for various AI/ML methods.
  • Ability to optimize AI/ML hyperparameters using automated grid searches and other methods.
  • Experience with computer vision problems, including image recognition, classification, and segmentation.
  • Ability to provide a portfolio of software and programs (e.g. GitHub) highlighting the breadth and depth of candidate's ability to author AI/machine learning solutions.
  • Physical Requirements Working Conditions Degree Requirement Listed degree qualification is required at time of application.

    Posting Date 01/21/2022

    Closing Date Open Until Filled Yes Special Instructions to Applicants

    The first consideration date for applications is 2/7/2022.

    Background Check Statement

    Applicants who are selected as final possible candidates must be able to pass a criminal background check.

    EEO Statement

    The University of Idaho (U of I) is an equal opportunity and affirmative action employer committed to assembling a diverse, broadly trained faculty and staff. Women, minorities, people with disabilities and veterans are strongly encouraged to apply. In compliance with applicable laws and in furtherance of its commitment to fostering an environment that welcomes and embraces diversity, U of I does not discriminate on the basis of race, color, religion, national origin, sex, age, sexual orientation, gender identity/expression, disability, genetic information or status as any protected veteran or military status in its programs or activities, including employment, admissions and educational programs.

    Applicant Documents

    Required Documents

  • Resume/CV
  • Cover Letter/Letter of Application
  • Optional Documents

    Supplemental Questions

    Required fields are indicated with an asterisk ().

  • How did you hear about this employment opportunity?
  • Academic Keys
  • Association of Public and Land Grant Universities (APLU)
  • Chronicle of Higher Education
  • Craig's List
  • Department of Labor/Job Service including Job Central or Idaho Works
  • Facebook
  • Higher Education Recruitment Consortium (HERC)
  • LinkedIn
  • National Association of State Universities and Land-Grant Colleges (website)
  • Newspaper
  • Professional Listservs (Ex: NACUBO, AAAE, ISMC, etc.)
  • UI Employee
  • UI Register
  • University of Idaho Website
  • Veterans in Higher Ed
  • Diverse: Issues in Higher Education
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  • Word of Mouth
  • Other Advertising Venue