We report a framework that enables the wide adoption of authentic research educational methodology at various schools by addressing common barriers. The guiding principles we present were applied to implement a program in which teams of students with complementary skills develop useful artificial intelligence (AI) solutions for researchers in natural sciences. To accomplish this, we work with research laboratories that reveal/specify their needs, and then our student teams work on the discovery, design, and development of an AI solution for unique problems using a consulting-like arrangement. To date, our group has been operating at New York University (NYU) for seven consecutive semesters, has engaged more than a hundred students, ranging from first-year college students to master's candidates, and has worked with more than twenty projects and collaborators. While creating education benefits for students, our approach also directly benefits scientists, who get an opportunity to evaluate the usefulness of machine learning for their specific needs.

翻译：我们提出一种框架，通过解决常见障碍，使真实研究教育方法能够在各类学校广泛采用。我们应用所提出的指导原则实施了一个项目，让具备互补技能的学生团队为自然科学领域的研究人员开发实用的人工智能（AI）解决方案。为实现这一目标，我们与研究实验室合作，由实验室明确其需求，随后学生团队以类似咨询的方式，针对独特问题进行AI解决方案的探索、设计与开发。迄今为止，我们团队已在纽约大学（NYU）连续运行七个学期，吸引了从大学新生到硕士候选人在内的百余名学生参与，并与超过二十个项目及合作者开展了合作。在为学生创造教育效益的同时，我们的方法也直接使科学家受益，他们有机会评估机器学习技术针对其特定需求的有效性。