BEGIN:VCALENDAR
VERSION:2.0
PRODID:icalendar-ruby
CALSCALE:GREGORIAN
X-WR-CALNAME:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Compe
 tition
X-WR-TIMEZONE:Eastern Time (US & Canada)
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707642171
DTSTART:20230110T163000Z
DTEND:20230110T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707644220
DTSTART:20230112T163000Z
DTEND:20230112T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707646269
DTSTART:20230117T163000Z
DTEND:20230117T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707648318
DTSTART:20230119T163000Z
DTEND:20230119T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707649343
DTSTART:20230124T163000Z
DTEND:20230124T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707651392
DTSTART:20230126T163000Z
DTEND:20230126T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707653441
DTSTART:20230131T163000Z
DTEND:20230131T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
BEGIN:VEVENT
DTSTAMP:20260520T161744Z
UID:tag:localist.com\,2008:EventInstance_41837707655490
DTSTART:20230202T163000Z
DTEND:20230202T180000Z
DESCRIPTION:Offered: IAP\n6 units (P/D/F)\, Undergraduate\, Tuesdays and Th
 ursdays from 11:30 am-1:00 pm.\nPrerequisite: Programming (e.g.\, Python) 
 at the level of 6.1010. Recommended prereqs: 6.3720\, 6.3900\, or 6.3730[J
 ]/IDS.012[J]. No background in biology required.\nInstructors: Caroline Uh
 ler (EECS)\, Paul Blainey (Biological Engineering)\, Jonathan Weissman (Bi
 ology)\n\nThe future of cancer care is immunotherapy — using our body’
 s immune system to eliminate tumors. While T cells\, our immune system’s
  fighter cells\, should recognize and kill growing tumors\, cancer cells s
 end signals to T cells that cause these fighter cells to malfunction. But 
 what if we could modify T cells to make them better at killing cancer cell
 s? In this class\, students will participate in a global cancer immunother
 apy data science challenge and apply their machine learning skills to help
  solve this key biological problem. The challenge is being run by the Eric
  and Wendy Schmidt Center at the Broad Institute of MIT and Harvard. Stude
 nts will learn the basics of cancer biology\, single-cell sequencing techn
 ology\, and data analysis needed to succeed in the challenge. Top-scoring 
 submissions will be validated in a lab at the Broad Institute\, and winner
 s will be eligible for monetary prizes totaling $50\,000 and paper authors
 hip.\n\nFor details on the challenge\, please visit the challenge website.
   To enroll in the class\, visit the MIT course catalog.
GEO:42.360931;-71.092731
LOCATION:26-168\, 26-168
SUMMARY:6.S099 Machine Learning Single-Cell Cancer Immunotherapy Competitio
 n
URL;VALUE=URI:https://calendar.mit.edu/event/6s099_machine_learning_single-
 cell_cancer_immunotherapy_competition
END:VEVENT
END:VCALENDAR