During the first year, this course meets daily for 15 weeks during the fall and spring semesters. Topics are presented through a mix of didactic lectures, workshops, and discussions focused on research papers. Students are expected to present papers and lead conversations in which the group analyzes research.
The course is divided into 5 sections:
- Experimental Biology teaches conceptual and practical aspects of 5 different research disciplines: imaging, genetics, biochemistry, genomics, and quantitative biology.
- Cancer Engineering provides students with a foundation in engineering principles that can be used to solve challenges in cancer biology and oncology. The curriculum includes 9 weeks of classes organized into three sections: Molecular and Nanoengineering; Cancer Imaging; and Genetic Engineering.
- Immunology familiarizes students with cellular, molecular, and biochemical aspects of the immune system and how immune responses function in physiology. It focuses on the development of the immune system and the biological functions of its major components.
- Entrepreneurship teaches the processes involved in developing a technology for the market, including understanding intellectual property; evaluating the market for a technology; building a basic financial model; establishing funding mechanisms; assessing regulatory issues; and developing a business plan.
- Cancer Biology teaches how to think about cancer as a disease and also as a biological problem. This course leverages the world-class research and clinical expertise at Memorial Sloan Kettering.
Developing the ability to present and discuss the results of your research in a coherent, logical and compelling fashion is an important feature of becoming a successful scientist. From the first through the fourth years in the program, all students are required to attend and participate in presentations that will help to develop these skills, from chalk talks in the first and second years, to formal graduate student seminars presented in years three and four. Each student presents his or her project, and fellow students provide critical feedback.
The Cancer Engineering Seminar Series and Cancer Engineering Research in Progress sessions are a collection of research seminars given by both external and internal scientists and engineers on emerging topics within the field of Cancer Engineering.
This curriculum has been structured to emphasize the foundations in Python and its four fundamental scientific computing libraries. This course also emphasizes two premier packages for statistical analyses and machine learning. This course wraps up with a capstone project to bring together all of these concepts in a practical and applied way. This course is structured with a two-day per week delivery. Active learning and classroom pair programming will be equally used and integrated to complement traditional lectures.
This course aims to teach Cancer Engineering students the fundamental statistical concepts underlying the most important research tools, how and when one can apply these tools as well as their strengths and weaknesses.