Training Board of The Mathematical Cognition and Learning Society. We represent undergraduate and graduate students, postdocs, teachers, and other trainees.
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ALT Flyer for MCLS Trainee December Special, with the following description: Speed Networking Events. Tuesday, December 3 at 4pm HKT / 7pm AEDT / 8am GMT / 9am CET AND at 11am EST / 8am PST / 4pm GMT / 5pm CET. To launch this year’s mentoring program, we will have two speed networking events on December 3rd. Join us for one or both events! The events will give you the opportunity to informally chat with fellow MCLS members, build connections, and explore potential mentor, mentee, and buddy matches! The networking event is optional - you can sign up for the mentoring program without attending the event!
ALT Flyer for MCLS Trainee December Special, with the following description: Speed Networking Events. Tuesday, December 3 at 4pm HKT / 7pm AEDT / 8am GMT / 9am CET AND at 11am EST / 8am PST / 4pm GMT / 5pm CET. To launch this year’s mentoring program, we will have two speed networking events on December 3rd. Join us for one or both events! The events will give you the opportunity to informally chat with fellow MCLS members, build connections, and explore potential mentor, mentee, and buddy matches! The networking event is optional - you can sign up for the mentoring program without attending the event!
ALT Flyer for MCLS Trainee December Special, with the following description: Speed Networking Events. Tuesday, December 3 at 4pm HKT / 7pm AEDT / 8am GMT / 9am CET AND at 11am EST / 8am PST / 4pm GMT / 5pm CET. To launch this year’s mentoring program, we will have two speed networking events on December 3rd. Join us for one or both events! The events will give you the opportunity to informally chat with fellow MCLS members, build connections, and explore potential mentor, mentee, and buddy matches! The networking event is optional - you can sign up for the mentoring program without attending the event!
ALT Flyer for MCLS trainee November Special: Pre- and Postdoctoral Funding Opportunities. Includes the following information: Join us to hear insights and advice on pursuing early career funding opportunities from: Andy Ribner (Assistant Professor, Chatham University), Nicole Scalise (Assistant Professor, Washington State University), and Lauren Westerberg (Postdoctoral Research Associate, University of Wisconsin-Madison). We will also share a working document of pre- and postdoctoral funding opportunities that may be of interest. *Note: This session will be centered on funding opportunities in the US.
ALT Flyer for MCLS trainee November Special: Pre- and Postdoctoral Funding Opportunities. Includes the following information: Join us to hear insights and advice on pursuing early career funding opportunities from: Andy Ribner (Assistant Professor, Chatham University), Nicole Scalise (Assistant Professor, Washington State University), and Lauren Westerberg (Postdoctoral Research Associate, University of Wisconsin-Madison). We will also share a working document of pre- and postdoctoral funding opportunities that may be of interest. *Note: This session will be centered on funding opportunities in the US.
ALT Flyer for MCLS trainee October Special: Creating an online experiment using jsPsych. Includes the following description: For this special, Vijay Marupudi (https://vijaymarupudi.com/) will guide you through designing an online experiment using jsPsych. Specifically, we will make a simple magnitude comparison interface, design an experiment using it, publish the study online, and understand the format of the data collected from the experiment (e.g., RT and accuracy). Some experience defining and using functions in R or Python and will be helpful.
ALT Flyer for MCLS trainee October Special: Creating an online experiment using jsPsych. Includes the following description: For this special, Vijay Marupudi (https://vijaymarupudi.com/) will guide you through designing an online experiment using jsPsych. Specifically, we will make a simple magnitude comparison interface, design an experiment using it, publish the study online, and understand the format of the data collected from the experiment (e.g., RT and accuracy). Some experience defining and using functions in R or Python and will be helpful.
