Special event: How to give a journal club.

UPDATE: We have a room: this event will occur Nov 11th at 3pm in 3N44A.

Journal clubs, such as ours, are popular during Graduate and Postdoc studies. And for good reason: journal clubs help us learn how to read peer-reviewed manuscripts, interpret the results, and – sometimes – be critical of the data. However, learning how to effectively lead a group of peers in this activity is an important skill which is often not formally taught as part of our academic training.

Towards this end, the Human Microbiome Journal Club is very excited to announce that on November 11th at 3pm in 3N44A we will have a special guest seminar  given by Dr. Mark McDermott. Dr. McDermott is a recently retired Professor of Pathology and Molecular Medicine here at McMaster. Throughout his career, Dr. McDermott has published >40 peer-reviewed manuscripts, including a seminal paper in mucosal immunology. On the 11th, Dr. McDermott will use this seminal paper (McDermott MR, & Bienenstock J.”Evidence for a Common Mucosal Immunologic System.“) to demonstrate how to present an effective journal club. Don’t worry if you’re microbe-foccused project hasn’t come across the mucosa literature yet; this event will focus more about how to present, than the in’s and out’s of mucosal immunology.

We look forward to drawing on Dr. McDermott’s experience and expertise at this special HMJC event! Formal presentation will begin at 3:00pm sharp (room TBA), followed by a chance to chat with Dr. McDermott at the Phoenix.

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2 Responses to Special event: How to give a journal club.

  1. Kerry Ivey says:

    Hello I would like to attend this event Where is it located, and do I need to register? Thank you

    Regards

    Kerry

    On Mon, Oct 17, 2016 at 6:39 AM, Human Microbiome Journal Club wrote:

    > Fiona Whelan posted: “Journal clubs, such as ours, are popular during > Graduate and Postdoc studies. And for good reason: journal clubs help us > learn how to read peer-reviewed manuscripts, interpret the results, and – > sometimes – be critical of the data. However, learning how t” >

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