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Generative Artificial Intelligence Fellow

Dartmouth College
Hanover, NH Full Time
POSTED ON 4/8/2024
Position Information

Posting date 02/08/2024
Closing date
Open Until Filled Yes
Position Number 1128703
Position Title Generative Artificial Intelligence Fellow
Department this Position Reports to Research Computing and Data Services
Hiring Range Minimum $66,200
Hiring Range Maximum $82,800
Union Type Not a Union Position
SEIU Level Not an SEIU Position
FLSA Status Exempt
Employment Category Regular Full Time w/end date
Scheduled Months per Year 9
Scheduled Hours per Week 40
Schedule
M-F, 8a-5p
Location of Position
Hanover, NH
4 Currier, 2nd Floor
Remote Work Eligibility? Hybrid
Is this a term position? Yes
If yes, length of term in months. 9
Is this a grant funded position? No
Position Purpose
The Generative Artificial Intelligence Fellow (GenAI-Fellow) at Research Computing and Data Services, ITC, Dartmouth, collaborates closely with faculty to advance research projects and ensures efficient GenAI technology utilization. The Fellow contributes to teaching projects that integrate GenAI tools and methodologies for a more enriched learning environment. Emphasizing continuous learning, they actively participate in problem-solving and project development under the mentorship of experienced ITC team members while providing guidance to student workers in navigating GenAI, coding complexities, and application development.
Description
Are you a trained data scientist proficient in programming with Python and R? Ready to be part of a dynamic team at Dartmouth's Research Computing and Data Services, ITC, where innovation meets impact? We're seeking a passionate individual in the upper valley to join us as a Generative Artificial Intelligence Fellow (GenAI-Fellow) to contribute to groundbreaking research projects and shape the use of artificial intelligence in academia.

Why Dartmouth:

At Dartmouth, innovation and collaboration thrive. As a GenAI-Fellow, you'll play a pivotal role in advancing impactful research through cutting-edge Generative Artificial Intelligence (GenAI) tools and methodologies.

Your Role:

As a key team member, you'll be at the forefront of project development, designing and implementing GenAI tools for data-driven faculty projects. Your expertise will provide crucial support to faculty projects, tackling new challenges with innovative AI techniques. Collaborate closely with faculty to establish best practices for GenAI integration in academic settings, ensuring the implementation of emerging projects.

Operational Excellence:

Support researchers in leveraging GenAI resources across campus, providing mentorship and direction to student workers. Contribute to staffing and recruitment efforts during designated hours and special events. Develop and document workflows to optimize operations and project management within the Research Informatics team.

Drive Innovation Independently:

Collaborate with the Research Informatics team on personal GenAI projects, participate in the development of AI toolkits, and actively engage in outreach activities. Your independent projects and innovations will align with and support GenAI tools and technologies for researchers, contributing to the creation of AI marketing materials.

Your Qualifications:

Bring your Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Showcase your proficiency in GenAI tools, coding (R, Python), and experience with machine learning frameworks (TensorFlow, PyTorch).

If you're passionate about shaping the future of AI in academia and thrive in a collaborative environment, we want to hear from you. Submit your application, along with a resume and cover letter today.

Join Dartmouth at the frontier of Generative Artificial Intelligence and make an impact today!
Required Qualifications - Education and Yrs Exp Masters or equivalent combination of education and experience
Required Qualifications - Skills, Knowledge and Abilities
  • Master's degree in Computer Science, Data Science, Artificial Intelligence, or a related field.
  • Experience using GenAI tools for data-driven research projects.
  • Proficient in coding (R, Python) for diverse applications.
  • Experience with the use of Machine Learning frameworks like TensorFlow and PyTorch.
  • Demonstrated track record in application development with a portfolio showcasing completed projects.
  • Proficient in employing data visualization tools and techniques.
  • Demonstrated creative problem-solving abilities, and in addressing intricate technical challenges.
  • Exhibits effective communication skills.
  • Adept at both independent work and collaborative team efforts, managing multiple projects concurrently.
  • Exhibits strong organizational skills with a keen attention to detail.
  • Exhibits a natural curiosity for exploring emerging technologies and methodologies.
Preferred Qualifications
Preferred Qualifications
  • 1-3 years of relevant post-Master's degree experience in research or applied AI environments.
  • Experience with using GenAI, Deep Learning frameworks, and Natural Language Processing (NLP) for projects.
  • Familiarity with agile development methodologies and version control systems, including Git.
  • Previous experience in an educational or research institution, collaborating on interdisciplinary projects.
  • Prior experience in research and publication in reputable journals or conferences.
  • Experience in mentoring to promote and cultivate a positive learning environment.
  • Demonstrated commitment to continuous learning and professional development in GenAI and related technologies.
Department Contact for Recruitment Inquiries Jonathan Kulp
Department Contact Phone Number 603.646.6110
Department Contact for Cover Letter and Title John Wallace
Department Contact's Phone Number 603.646.1412
Equal Opportunity Employer
Dartmouth College is an equal opportunity/affirmative action employer with a strong commitment to diversity and inclusion. We prohibit discrimination on the basis of race, color, religion, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications by members of all underrepresented groups are encouraged.
Background Check
Employment in this position is contingent upon consent to and successful completion of a pre-employment background check, which may include a criminal background check, reference checks, verification of work history, conduct review, and verification of any required academic credentials, licenses, and/or certifications, with results acceptable to Dartmouth College. A criminal conviction will not automatically disqualify an applicant from employment. Background check information will be used in a confidential, non-discriminatory manner consistent with state and federal law.
Is driving a vehicle (e.g. Dartmouth vehicle or off road vehicle, rental car, personal car) an essential function of this job? Not an essential function
Special Instructions to Applicants
This position is a 9-month term position.

Dartmouth College has a Tobacco-Free Policy. Smoking and the use of tobacco-based products (including smokeless tobacco) are prohibited in all facilities, grounds, vehicles or other areas owned, operated or occupied by Dartmouth College with no exceptions. For details, please see our policy.
Additional Instructions
We strongly encourage applicants to include a link to their GitHub portfolio of relevant work.

This portfolio might encompass peer-reviewed academic publications (submitted or accepted), Python data science/GenAI projects, and/or a detailed description of faculty-driven projects.

This is a 9-month term position, and we want to highlight that the total compensation package includes benefits.
Quick Link
Key Accountabilities

Description
Project Development

  • Designs, codes, and implements GenAI tools for data-driven projects
  • Provides support to faculty projects (both research and teaching) including project definition, scoping, development, and delivery.
  • Research solutions to new project challenges utilizing innovative AI techniques.
  • Collaborates with faculty and learning designers to develop best practices for GenAI integration within academic and research settings,
  • Ensures implementation of emerging projects and documents associated workflows.
Percentage Of Time 75%
Description
GenAI Operational Support

  • Facilitates researchers in leveraging GenAI resources and technologies across the campus.
  • Provides training, mentoring, direction, and supervision to student workers, assisting in their comprehension and application of AI and coding principles.
  • Assists the Research Informatics team in staffing and recruitment efforts during designated hours and special public events.
  • Develops and documents workflows to optimize operations and project management within the Research Informatics team.
Percentage Of Time 10%
Description
Independent Projects and Innovation

  • Collaborates with the Research Informatics team on personal projects in GenAI and related fields to align and support GenAI tools and technologies for researchers.
  • Participates in the development of AI toolkits.
  • Generates AI marketing materials and actively participates in outreach activities to promote AI resources, tools, and projects both internally and externally.
  • Engages in exploratory work focused on solving real-world problems using innovative AI solutions.
Percentage Of Time 10%
Description
Other duties as assigned
Percentage Of Time 5%
-

-- Demonstrates a commitment to diversity, inclusion, and cultural awareness through actions, interactions, and communications with others.
-- Performs other duties as assigned.

Dartmouth College is an equal opportunity/affirmative action employer with a strong commitment to diversity and inclusion. We prohibit discrimination on the basis of race, color, sex, age, national origin, sexual orientation, gender identity or expression, disability, veteran status, marital status, or any other legally protected status. Applications by members of underrepresented groups are encouraged.


 

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