[bioundgrd] FW: NSE Special Subjects for Spring 2022!

[Joshua Stone]

Begin forwarded message:

From: Brandy Baker <brandyb at mit.edu<mailto:brandyb at mit.edu>>
Subject: Re: NSE Special Subjects for Spring 2022!
Date: January 12, 2022 at 8:43:33 AM EST

NSE has a special subject and new ML subject offered this Spring that you might be interested in.
22.S095 Radiation and Life (Undergraduate) – Limited enrollment, but there are still spots open!
22.C01/22.C51 (Formerly 22.042/22.42) Modeling with Machine Learning: Nuclear Science and Engineering Applications

Details below.

22.S095 Radiation and Life – Applications of Radiation Sources in Medicine, Research, & Industry
3 Units, Undergraduate level, P/D/F graded
Prerequisites - None

What are the myriad of uses of radiation sources? How do we control their uses to protect workers? In this discovery subject, students will be introduced to the basics of ionizing and non-ionizing radiation, radiation safety and protection and an overview of the variety of health physics applications especially as it pertains to the medical field and to radioactive materials research in academia. This class will cover the basic physics of ionizing and non-ionizing radiation, known effects on the human body and the techniques to measure those effects. This class will introduce common radiation-based medical imaging techniques and therapies. Students will engage in a variety of hands-on projects, demonstrations and experiments that will introduce them to standard techniques and practices in typical medical and MIT research lab environments where radiation is used. This is a great class to take if you are currently doing work in medical, biological, or nuclear areas at MIT, or if you are interested in later doing a UROP, Co-Op or Internship that will involve working with radiation sources and detectors. The course is geared toward undergraduates as an introduction to how radiation sources and radioactivity are used by researchers in most majors at MIT.

Course Meeting Times
Lectures: 2 sessions / week, 1.5 hours / session,  N52 – 495
Wedsnesday (Lecture): 9:30-11:00AM
Friday (Lab): TBD

Instructor – Tolga Durak, PhD, PE, Managing Director, Environment Health and Safety (tdurak at mit.edu<mailto:tdurak at mit.edu>)

Limited Enrollment – there are spots still open!  If you miss pre-registration, add yourself to the waitlist!
https://registrar.mit.edu/registration-academics/academic-requirements/limited-enrollment-waitlists

22.C01/22.C51 (Formerly 22.042/22.42) Modeling with Machine Learning: Nuclear Science and Engineering Applications
Level: Undergrad (22.C01) and Grad (22.C51)
Co-register for 6.C01 (Undergrad) or 6.C51 (Grad)
Building on core material in 6.C51, focuses on applying various machine learning techniques to a broad range of topics which are of core value in modern nuclear science and engineering. Relevant topics include machine learning on fusion and plasma diagnosis, reactor physics and nuclear fission, nuclear materials properties, quantum engineering and nuclear materials, and nuclear security. Special components center on the additional machine learning architectures that are most relevant to a certain field, the implementation, and picking up the right problems to solve using a machine learning approach. Final project dedicated to the field-specific applications. Students taking graduate version complete additional assignments. Students cannot receive credit without simultaneous completion of the core subject 6.C51.
http://student.mit.edu/catalog/search.cgi?search=22.C01
http://student.mit.edu/catalog/search.cgi?search=22.C51

Instructor: Prof Mingda Li (mingda at mit.edu<mailto:mingda at mit.edu>)


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