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@Winnipeg

多大的ES二年级后有一个Biomedical Systems Engineering的方向….,, 滑大应该也有。

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EngSci’s Biomedical Systems Engineering major prepares students for graduate studies and careers with an interdisciplinary curriculum in engineering and life sciences.
Full Story:
https://engsci.utoronto.ca/program/majors/biomedical-systems/
(#16049788@0)
Last Updated: 4-13
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Replies, comments and Discussions:

  • 枫下家园 / 望子成龙 / 谁知道黄仁勋说的“生命工程”哪个学校比较👌？或者说这个专业到底是干啥的？ -danielw1(Daniel); 4-13 {1262} (#16049681@0)
    美國繪圖晶片業巨擘輝達（Nvidia）執行長黃仁勳一舉一動都是焦點，他日前出席2024年世界政府峰會時，被問到如果站在科技的前端，人們到底應該學習什麼？他回應，「學習電腦的時代過去了，生命科學是未來」。
    Full Story:
    https://tw.news.yahoo.com/%E5%AD%B8%E9%9B%BB%E8%85%A6%E7%9A%84%E6%99%82%E4%BB%A3%E9%81%8E%E5%8E%BB%E4%BA%86-%E5%A4%A7%E5%AD%B8%E8%A9%B2%E5%BF%B5%E4%BB%80%E9%BA%BC%E7%A7%91%E7%B3%BB-%E9%BB%83%E4%BB%81%E5%8B%B3%E7%B5%A6%E7%AD%94%E6%A1%88-%E5%A6%82%E6%9E%9C%E6%9C%89%E9%87%8D%E6%96%B0%E9%81%B8%E6%93%87%E7%9A%84%E6%A9%9F%E6%9C%83-%E9%80%99%E9%A0%98%E5%9F%9F%E6%89%8D%E6%98%AF%E6%9C%AA%E4%BE%86-101347018.html
    • 只有生命科学，生物工程。生命宝贵，断不可拿来做工程 -papyrus(古道西风); 4-13 (#16049693@0)
      • 听说斯坦福在搞，不知道怎么搞？ -danielw1(Daniel); 4-13 (#16049769@0)
    • 不太懂。我知道现在有一些在研究建立基因组数据库，结合了遗传学，生物学，计算机科学等跨领域学科的运用。大概就是研究基因排序，把个人基因和数据库进行比对，一个是能够找出罕见遗传病，诊断治疗，还能够预测潜在遗传病等。 -humankindyyds(枫木森林); 4-13 (#16049700@0) +1
      • 我也这么想. 有人说是做器官模型，然后治病啥的. 搞不懂黄的脑子里想的是啥. -danielw1(Daniel); 4-13 (#16049767@0)
    • 多大的ES二年级后有一个Biomedical Systems Engineering的方向….,, 滑大应该也有。 -cookie321(cookie); 4-13 {717} (#16049788@0)
      EngSci’s Biomedical Systems Engineering major prepares students for graduate studies and careers with an interdisciplinary curriculum in engineering and life sciences.
      Full Story:
      https://engsci.utoronto.ca/program/majors/biomedical-systems/
      • 有意思. 👍，谢谢 -danielw1(Daniel); 4-13 (#16049867@0)
        • 这个是Mcmaster的Biotechnology…. -cookie321(cookie); 4-13 {1193} (#16049881@0)
          Gain the expertise and practical laboratory skills necessary to innovate in genetic engineering and bioprocessing for the advancements of tomorrow.
          Full Story:
          https://www.eng.mcmaster.ca/sept/degree-options/biotechnology/#:~:text=Program%20highlights&text=Study%20genetic%20engineering%3B%20cell%20biology,genomics%2C%20proteomics%2C%20and%20bioinformatics.
          • 记得去年夏天，看到一报道这个学习拿AI找到了什么病毒喝对人体有益的微生物啥的. 不知道是不是黄说的“生命工程” -danielw1(Daniel); 4-13 (#16049902@0)
            • 黄大仙现在当红，说啥都对，都是指路明灯。。。比尔盖茨不也搞生物制药…..除非孩子自己有兴趣去选择，否则当八卦听听吃吃瓜就好了，LOL。。。 -cookie321(cookie); 4-13 (#16049912@0)
              • 现在科学发展这么快，大人都懵，高中生还不行，需要参考大人，老师们的意见 -danielw1(Daniel); 4-13 (#16049927@0) +1
                • 目标不清的，迟熟慢热的孩子，进前一两年上基础课高年级再分方向的综合性大学或专业更好。 -cookie321(cookie); 4-13 (#16049930@0) +1
    • 秦始皇搞的长生不老算不算一个分支？ -sweettooth(闲逛); 4-13 (#16049799@0)
      • 可惜老头每挺到现在. -danielw1(Daniel); 4-13 (#16049868@0)
    • 他主要是感慨AI在大分子蛋白质生成和预测上的应用。其实还有一个方向上处于萌芽阶段的就是DNA计算机，现在的存储单元和计算是基于硅的，将来可用DNA -narra(万儿八千); 4-13 {310} (#16049803@0)
      • 哦！学习了. 这方面哪个学校比较厉害？ -danielw1(Daniel); 4-13 (#16049879@0)
        • computational biology, bioinformatics, 这两专业比较厉害的是University of Toronto,UBC,McGill ,University of Alberta -narra(万儿八千); 4-13 {1914} (#16050186@0)

          Canada has several universities known for their strong programs in computational biology, bioinformatics, and related fields. Here are a few notable ones:

          1. University of Toronto: The University of Toronto is one of Canada's top research universities and offers programs in computational biology, bioinformatics, and related areas through departments such as Computer Science, Molecular Genetics, and Biochemistry.

          2. University of British Columbia (UBC): UBC is another leading Canadian institution with strong programs in computational biology and bioinformatics. The Department of Computer Science and the Department of Biochemistry and Molecular Biology are particularly active in this area.

          3. McGill University: Located in Montreal, McGill University has a vibrant research community in computational biology and bioinformatics. The McGill Centre for Bioinformatics is a hub for interdisciplinary research in this field.

          4. University of Alberta: The University of Alberta in Edmonton has notable strengths in both computer science and biological sciences, making it a good choice for interdisciplinary research in computational biology and bioinformatics.

          5. Simon Fraser University (SFU): SFU, located near Vancouver, offers programs in computing science and biological sciences, providing a strong foundation for research at the intersection of these fields.

          These universities have strong research communities, well-established faculty, and excellent resources for students interested in pursuing research in AI-driven protein structure prediction and its applications in biology. It's a good idea to explore the specific research projects and faculty members in each university to find the best fit for your interests and career goals.

        • 多大在computational biology最强，一些比较有名的学者教授 -narra(万儿八千); 4-13 {2222} (#16050207@0)

          1. Gary Bader (University of Toronto): Dr. Gary Bader is a Professor in the Department of Molecular Genetics at the University of Toronto. He is well-known for his work on computational methods for analyzing biological networks, particularly protein-protein interaction networks.

          2. Quaid Morris (University of Toronto): Dr. Quaid Morris is a Professor in the Donnelly Centre for Cellular and Biomolecular Research and the Department of Molecular Genetics at the University of Toronto. He has made significant contributions to computational biology, genomics, and machine learning, with a focus on developing algorithms for analyzing biological data.

          3. Anne-Claude Gingras (University of Toronto): Dr. Anne-Claude Gingras is a Senior Investigator at the Lunenfeld-Tanenbaum Research Institute and a Professor in the Department of Molecular Genetics at the University of Toronto. Her research interests include computational analysis of protein interactions and complex assembly.

          4. Alan Moses (University of Toronto): Dr. Alan Moses is an Associate Professor in the Department of Cell & Systems Biology and the Department of Computer Science at the University of Toronto. He is known for his work on computational methods for studying gene regulation and evolutionary genomics.

          5. Nicholas Provart (University of Toronto): Dr. Nicholas Provart is a Professor in the Department of Cell & Systems Biology at the University of Toronto. His research focuses on computational analysis of gene expression data and systems biology approaches to understanding plant development and response to environmental stresses.

          6. Gary D. Bader (University of Toronto): Dr. Gary D. Bader is another notable scholar at the University of Toronto. His research interests lie in computational biology, particularly in the areas of network biology and systems biology.

          These scholars have made significant contributions to advancing the field of computational biology through their research, publications, and mentorship within Canada and beyond.

          • 谢谢，这些研究用AI比传统更有效？ -danielw1(Daniel); 4-13 (#16050687@0)
            • 看看这个例子： DeepMind新一代AlphaFold登场，超越蛋白质折叠，将推动下一个“数字生物学”时代到来 -narra(万儿八千); 4-13 {483} (#16050699@0)
              颠覆生命科学的 AlphaFold 又更新了。
              Full Story:
              https://36kr.com/p/2499183744194691
              • 很有可能👍是这个！谢谢大神🙏 -danielw1(Daniel); 4-14 (#16050850@0)
    • 感觉用芯片的AI公司更有说服力吧？山姆奥特曼啥意见？ -deep_breath(三季人); 4-13 (#16049896@0)
      • ？？？ -danielw1(Daniel); 4-13 (#16049904@0) +1
        • 我意思是英伟达造芯片的，指导用芯片的搞AI的人什么行业有前途，迷惑 -deep_breath(三季人); 4-13 {46} (#16049916@0)

          不恰当的比喻就是养猪的告诉厨师做什么肉菜好吃
          • 我觉得黄想用他的AI芯片建3D人体器官模型. 都是自己瞎猜的. 看看有没有懂生命工程这一块儿的，可以理解黄想干啥. -danielw1(Daniel); 4-13 (#16049925@0)
    • 黄皮衣发财了想做黄大仙产生不老，于是忽悠年轻人炼丹，谁信了真去学生物就掉坑里了。 -westisland(年华虚度空有一身疲倦); 4-13 (#16049936@0) +1
      • 马斯克的人脑接口可不是忽悠人的. 黄在做AI芯片前是有做过研究的. 硬件都出来了，应该不是忽悠 -danielw1(Daniel); 4-13 (#16049939@0)
    • 和医学研究相关专业约翰霍普金斯应该很不错。 -bststl(bststl); 4-13 (#16050697@0) +1
      • 谢谢指点 -danielw1(Daniel); 4-14 (#16050851@0)

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