Calendar of events
Friday, January 21, 2022
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PhD training: “Research Software Engineering with Python” courseRuns from Monday, January 17 to Friday, January 28. The Alan Turing Institute is offering postgraduate students the opportunity to attend an online “Research Software Engineering with Python” course between 17 – 28 January 2022. The course is open to students who are interested in learning how to construct reliable, readable, efficient research software in a collaborative environment. There is no cost for the course if you are selected to take part, so if you would like to apply for a place and/or find out more information about the course, please see the following link: https://www.eventsforce.net/turingevents/frontend/reg/thome.csp?pageID=50389&ef_sel_menu=733&eventID=152 |
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Warwick i2i Impact programme for Early Researchers, PhD and masters studentsOnline - events running on 19, 21, 26, 28 January 2022Runs from Wednesday, January 19 to Friday, January 28. The next programme will take place online on the 19th, 21st, 26th and 28th January 2022 and is aimed towards masters, PhD, post-doctoral and early career researchers working in any area of science, technology, engineering and mathematics, including life sciences and healthcare. Each workshop focuses on a different topic which include:
Contact: Tim Francis |
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Guest Speaker: Ensembled Preferences, Dr Antonia Krefeld-SchwalbOn-line Email c.j.johnstone@warwick.ac.uk for linkSpeaker: Dr Antonia Krefeld-Schwalb, Rotterdam School of Management, Erasmus University Follow on Twitter @antoniakrefeld Title: Ensembled Preferences Host: Dr Emmanouil Konstantinidis Abstract: Preference elicitation tasks are generally considered the gold standard of preference measurement. For example, intertemporal preferences elicited in the laboratory have been associated with various aspects of maintaining a healthy lifestyle (BMI, Amlung et al., 2016; MacKillop & Kahler, 2009; Chapman & Coups, 1999) and consumer financial decisions (Li et al., 2015; Meier & Sprenger, 2012; Atlas et al., 2017). Recently, evidence has accumulated that the use of preference elicitation tasks is associated with several problems related to the models used for measurement (Krefeld-Schwalb et al., 2021), respondent behavior in the task (Li et al., 2021), and the effects of the context and settings of the task (Hardisty et al., 2012; Read et al., 2017), which affect the predictive validity of the measures. As a way to overcome these problems, we propose combining multiple preference elicitation tasks in what we call an ensembled-preference approach. This approach also allows for multiple sources of unexplained variance to be accounted for in the preference elicitation tasks. See archive of Previous speakers here Email: Catherine Johnstone for a link . |