Artificial Intelligence in Health Care Research Fellowship

The Artificial Intelligence in Health Research Fellowship is a unique program focused on project-based learning that combines cutting-edge technology and innovative research to tackle some of the biggest challenges in healthcare today.

Our aim is to provide a dynamic learning environment that empowers students, researchers, and healthcare professionals to shape how artificial intelligence (AI) and machine learning can improve healthcare outcomes and advance medical research.

The No-Code Track and the Computer Science Track are two distinct pathways within the Artificial Intelligence in Health Research Fellowship program.

The No-Code Track is designed for individuals who have an interest in AI and machine learning but may not have a background in computer science or programming. This track will focus on the practical applications of AI in the healthcare domain and will utilize low-code or no-code platforms to build and deploy AI models. Participants will learn how to use tools and platforms that allow them to build and deploy AI models without writing any code, making it easier and more accessible for those without a technical background.

The Computer Science Track, on the other hand, is designed for individuals with a background in computer science and programming. This track will delve into the technical aspects of AI and machine learning and will focus on the development and deployment of AI models using programming languages such as Python and TensorFlow. Participants in this track will learn how to build and train AI models from scratch and will be able to apply their skills and knowledge to more complex AI projects.

Both tracks will provide participants with the opportunity to work on real-world projects and collaborate with other fellows, researchers, and healthcare professionals. The goal of both tracks is to empower individuals with the skills and knowledge to use AI to advance healthcare and medical research.

Key Benefits:

• Develop skills and expertise in AI and machine learning

• Work on real-world projects in the healthcare domain

• Collaborate with leading researchers, healthcare providers, and technology companies

• Expand your network and make valuable connections

• Gain experience in project management and team collaboration

Eligibility for the No-Code Track:

• A background in healthcare or life sciences is preferred but not required

• A strong interest in AI and machine learning

• Basic computer skills

• Ability to work effectively in a team environment

• Excellent communication and presentation skills

Eligibility for the Computer Science Track:

• A bachelor's degree in computer science, engineering, mathematics, or a related field

• Strong programming skills in languages such as Python or TensorFlow

• Strong interest in AI and machine learning

• Ability to work effectively in a team environment

• Excellent communication and presentation skills

In both tracks, the Artificial Intelligence in Health Research Fellowship is open to students, researchers, and healthcare professionals who are passionate about using AI to advance healthcare and medical research. Applicants should have a strong problem-solving and analytical skills, as well as the ability to work effectively in a team environment and communicate effectively.

Program Structure

The Artificial Intelligence in Health Research Fellowship is a 1-2 year program that combines project-based learning with collaborative learning. The program structure is as follows:

1. Virtual Learning Environment: The program is delivered virtually and participants will have access to online resources, including instructional videos, readings, and interactive exercises.

2. Project-Based Learning: Participants will work on real-world projects that focus on the application of AI in the healthcare domain. They will be able to choose between the No-Code Track or the Computer Science Track, depending on their background and interests.

3. Collaborative Learning: Participants will work in teams and have opportunities to network and collaborate with other fellows, researchers, and healthcare professionals. They will be able to share their experiences, ask questions, and receive feedback from their peers and mentors.

4. Mentorship and Technical Support: Participants will have access to mentors who are experts in the field of AI and machine learning. These mentors will provide guidance and support throughout the program, helping participants to overcome technical challenges and achieve their goals.

5. Workshops and Guest Speakers: Participants will attend workshops and hear from guest speakers who are experts in the field of AI and machine learning. These speakers will provide insights and inspiration on how to apply AI to advance healthcare and medical research.

The program is structured to provide a dynamic and immersive learning experience that will challenge participants to develop their skills and knowledge in AI and machine learning. The goal is to equip participants with the skills and knowledge they need to make a positive impact in the healthcare and medical research communities.

How to Apply

To apply, candidates should visit the program's website and submit their application, including their resume, transcripts, and a personal statement. There is a rolling deadline for applications. The program's admission committee will review all applications and select participants based on their qualifications and fit for the program.