Faculty Position in Data Science

Key Skills

Aartificial intelligence, Data science techniques, Effective communication skills, Large Language Models - LLMs, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow

Job Description

Responsibilities

The Department of Pediatric and Adolescent Medicine (DPAM) is seeking an innovative and analytical data science faculty member with a focus on research to join our dynamic team. The ideal candidate will have extensive experience in leveraging electronic health records (EHRs)-based AI including Natural Language Processing (NLP) technologies with large language models (LLMs) and Generative AI experience preferred to drive data-driven decisions and solutions. They should have a robust understanding of AI modeling, EHRs, and AI bias and a demonstrated track record in applying detection and mitigation strategies to create fair and ethical AI models. The role entails designing and implementing cutting-edge algorithms, developing predictive models, and working collaboratively to ensure our artificial intelligence systems are effective, safe, and unbiased, and contribute to our strategic goals. 

Responsibilities:

• Research and Development: Conduct research and development activities in the field of NLP, AI, and generative AI (LLM) to enhance asthma management using Electronic Health Records.
• AI for EHRs: Apply NLP and AI techniques to extract and analyze relevant information from EHRs for better patient care and treatment strategies.
• AI Bias Mitigation: Investigate and implement methods to mitigate bias in AI models, ensuring fair and equitable practices across diverse pediatric patient populations
• Model Development: Design, develop, and evaluate AI models, including but not limited to deep learning, machine learning, and generative AI models, for processing clinical text data in EHRs.
• Data Preprocessing: Work with the data team to preprocess and prepare clinical text data from EHRs for AI model training and validation.
• Performance Evaluation: Evaluate the performance of AI models and algorithms and iterate on improvements to achieve state-of-the-art results in diverse pediatric diseases.
• Collaboration: Collaborate with cross-functional teams, including healthcare professionals, data scientists, and software engineers, to integrate AI-based solutions into practical applications for diverse disease management.
• Priorities: Support diverse AI projects in Pediatrics according to strategic priorities and guidance from DPAM AI Advisory Committee and DPAM AI Program leadership

We are excited to welcome a passionate data science faculty member to our research group and contribute to groundbreaking advancements in clinical care and research through the innovative use of AI and NLP in Electronic Health Records and mitigating AI bias. A successful candidate will have the opportunity to work on challenging projects and collaborate with leading experts in the field. If you are passionate about leveraging AI for healthcare and want to make a meaningful impact in the lives of pediatric patients, we encourage you to apply and join Pediatric AI Program.

At Mayo Clinic, we believe there is a better path to healing that humanizes the practice of health care and inspires hope in the people who need it most. Our unified mission is to provide the best patient care, backed by our expertise and supported by innovation in education, research and practice, to bring hope and healing in times of need. We embrace collegial relationships among campuses (Arizona, Florida and Minnesota) allowing for best practices and innovation to help solve the most serious complex medical challenges-one patient at a time. 

We support a vibrant and diverse research enterprise, with programs in basic, translational, clinical, population, and data sciences. In 2022, the institution received over $679 million in extramural research awards, supplemented with over $421 million of institutional support. Laboratories and shared resource facilities are state-of-the-art, including those for microscopy and imaging, cell and molecular biology, animal models, production of iPS cells and clinical grade MSCs, biomedical engineering and mathematics, materials testing, a Medical Genomics Facility, a Mouse Modeling Facility, Molecular and Microscopic Core Facilities, and unique Human Disease Tissue Banks. Mayo Clinic supports innovation and has a wealth of resources available – including an integrated health record.

Mayo Clinic offers a highly competitive compensation package. Additional benefits for faculty at Mayo Clinic include intramural funding opportunities for research and innovation. We provide an outstanding, comprehensive benefits package that includes plenty of options for medical, dental and vision care; flexible spending accounts; life insurance; short- and long-term disability coverage; travel allowance; generous time away; and more! We are proud to be among the few U.S. companies to provide a pension benefit at no cost to employees plus you can add the Mayo 403(b) plan which features an employer match.

Qualifications

• Educational Background: A Ph.D. in Computer Science, Data Science, Artificial Intelligence, NLP, or a related field, with a strong academic record.
• NLP and AI Expertise: Demonstrated expertise in Natural Language Processing and AI, with a focus on applying these technologies to healthcare or medical domains.
• AI Bias: Proven experience in addressing AI bias and implementing strategies for fair and ethical AI applications.
• Generative AI (LLM): Familiarity with Generative AI models, particularly Language Models (LLM), and their applications in healthcare (not required, but preferred).
• Programming Skills: Proficiency in programming languages commonly used in AI and NLP, such as Python, TensorFlow, PyTorch, or similar frameworks.
• Research Publications: A track record of publications in reputable conferences or journals related to AI, NLP, or healthcare informatics is desirable.
• Collaboration: Excellent interpersonal skills with the ability to work effectively in a team-oriented research environment.

Applications should include a full CV/Bibliography, statement of research interests, statement of contributions to equity/inclusion/diversity, and the names/contact information of five references.