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<p class="MsoNormal">Hi GAPS,</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">We are happy to invite you to join a brand-new monthly seminar series, directly targeted at Early Career Scientists! The first of these will take place tomorrow<b>, November 15th at 1PM in the MOB auditorium</b> for those of you onsite
(light snacks will be provided) and on Zoom for those that aren’t (information listed below). The seminar will be structured as a 40 minute talk followed by 15 minutes for you to ask any and all questions you might have for the speaker.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">The seminars will initially focus on machine learning and its connections with the physics we do here at TRIUMF, and we are happy to be hosting Dr. Ben Nachman as our first speaker. Dr. Nachman is a staff scientist at Lawrence Berkeley
National Laboratory and leader of the Machine Learning for Fundamental Physics Group in the Physics Division. More information about the talk and zoom coordinates can be found below. Looking forward to seeing you tomorrow!</p>
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<p class="MsoNormal">-Your GAPS, on behalf of the Early Career Talks organizing committee</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Speaker: Dr. Ben Nachman (Lawrence Berkeley National Laboratory) (attending remotely)</p>
<p class="MsoNormal">Title: Phystatistics: The Rise of the Data Physicist</p>
<p class="MsoNormal">Abstract: Across the physical sciences, there has been a shift in paradigm from a theory-driven to a data-driven era. In this new regime, we let the data speak for themselves by using modern machine learning tools unimaginable prior to
the deep learning revolution of the last decade. At the same time, the physical sciences face unique challenges that require dedicated solutions to maximize the potential for discovery. Now, more than ever, we need a new kind of researcher - a phystatistician
(like biostatistician) or a data physicist (like data scientist). In this talk, I’ll describe unique challenges faced by phystatisticians and how innovative, reproducible, and scalable methodologies and scientific software are enabling researchers to harness
the power of modern machine learning for discoveries in the physical sciences.</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal">Zoom: <a href="https://ubc.zoom.us/j/61407832638?pwd=VN8tBA3D0SxMzsb7uXwIGbY5p6CBME.1">
https://ubc.zoom.us/j/61407832638?pwd=VN8tBA3D0SxMzsb7uXwIGbY5p6CBME.1</a></p>
<p class="MsoNormal">Meeting ID: 614 0783 2638<br>
Passcode: 325537</p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><a href="http://gaps.triumf.ca/" title="http://gaps.triumf.ca">gaps.triumf.ca</a><o:p></o:p></p>
<p class="MsoNormal">Follow us on Instagram at <a href="https://www.instagram.com/triumfgaps/" title="https://can01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fwww.instagram.com%2Ftriumfgaps%2F&data=05%7C02%7Cgaps%40triumf.ca%7C41f7da4e85c643a8bd7f08dd04e68665%7Cc20535109cb34679a2d38f442e03b587%7C1%7C0%7C638672110324560177%7CUnknown%7CTWFpbGZsb3d8">triumfgaps</a><o:p></o:p></p>
<p class="MsoNormal"><o:p> </o:p></p>
<p class="MsoNormal"><i>TRIUMF is located on the traditional, ancestral, and unceded territory of the x</i><i><span style="font-family:"Arial",sans-serif">ʷ</span>məθk</i><i><span style="font-family:"Arial",sans-serif">ʷ</span>əy</i><i><span style="font-family:"Arial",sans-serif">̓</span>əm (Musqueam)
people, who for millennia have passed on their culture, history, and traditions from one generation to the next on this site.</i></p>
<p class="MsoNormal"><o:p> </o:p></p>
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