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<p class="MsoNormal"><span style="font-family:"Arial",sans-serif">Hello Everyone,<br>
<br>
I am recruiting students for several positions (MSc, MA, PhD, postdoc) <br>
students who want to study the impact of tech in cities as well as <br>
citizen science.<br>
<br>
Smart Cities (MA/MSc)<br>
I have a position for a masters student (MA/MSc) to look at one or more <br>
of the following: 1. Spatial Inequity in the Smart City; 2. Who is <br>
Planning, Measuring and Operating the Smart City in Canada (where smart <br>
city implementation activities are housed inside city governments to <br>
better understand how this implementation process is administered and <br>
governed); and 3. Are smart cities open cities (comparing smart city <br>
goals, types of hardware, software and algorithms used, the use of data <br>
and its input back into municipal decision-making, and outcomes of <br>
implementation)?. The first requires GIS. The second and third require a <br>
combination of surveys, case studies, and ethnography. The fourth will <br>
require knowledge of or ability to learn about machine learning algorithms.<br>
<br>
Historical Weather Citizen Science (MSc)<br>
A collaboration between geographers, archivists, and atmospheric <br>
scientists at McGill has built a citizen science platform that <br>
encourages individuals to transcribe the hand written records of the <br>
McGill Observatory. These constitute the most complete set of historical <br>
weather observations of Canada. It is comprised of ~4 million <br>
observations on about 10,000 ledger sheets. Called DRAW (Data Rescue and <br>
Archives Weather - citsci.geog.mcgill.ca) individuals have transcribed <br>
about 200K observations so far. I have a position for an MSc student who <br>
will conduct research on the people who are contributing to the site, in <br>
terms of education (how much they know and learn about weather), <br>
motivation (how do we motivate them to continue contributing), and <br>
engagement (how much, how long). It will require some computer <br>
programming but that can be learned.<br>
<br>
Social Media Harvesting and Analysis of Weather Tweets (MSc, postdoc)<br>
I have a position for a MSc student to build a platform for data <br>
harvesting, NLP and sentiment analysis of social media related to <br>
extreme weather events. The Meteorological Service of Canada has funded <br>
a two year project to attempt to correlate how the public responds to <br>
extreme weather events with what they hear about from official and <br>
peri-official channels. Their hope is to be able to tone their messages <br>
based on likely public response. This also could be a position for a <br>
postdoc to manage the project. Either position will require significant <br>
computer skills, although the great thing about a project like this is <br>
the ready availability of software libraries (e.g., in Python, JS, R) to <br>
handle the "heavy lifting" in terms of coding.<br>
<br>
Artificial Intelligence and Algorithms in Civic Governance (MAs, MScs, <br>
PhDs, and postdocs)<br>
This one is contingent on funding. I hope to be recruiting MAs, MScs, <br>
PhDs, and postdocs to conduct research on the use, value, impact, and <br>
governance of AI and algorithms in cities. These positions will require <br>
a variety of skills--some will be on the more media studies end; some <br>
will be social science; some will be highly computational (GeoAI, <br>
spatial data science). There also would be funding for 1-2 postdocs, one <br>
to manage the project and one to conduct computational research on the <br>
impact of machine learning, neural networks on civic participation.<br>
<br>
The deadline for posting is Dec. 31. Email me or have your students <br>
email me for further details.<br>
<br>
Prof Sieber</span><o:p></o:p></p>
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