<html xmlns:v="urn:schemas-microsoft-com:vml" xmlns:o="urn:schemas-microsoft-com:office:office" xmlns:w="urn:schemas-microsoft-com:office:word" xmlns:m="http://schemas.microsoft.com/office/2004/12/omml" xmlns="http://www.w3.org/TR/REC-html40"><head><meta http-equiv=Content-Type content="text/html; charset=us-ascii"><meta name=Generator content="Microsoft Word 12 (filtered medium)"><style><!--
/* Font Definitions */
@font-face
{font-family:"Cambria Math";
panose-1:2 4 5 3 5 4 6 3 2 4;}
@font-face
{font-family:Calibri;
panose-1:2 15 5 2 2 2 4 3 2 4;}
@font-face
{font-family:Consolas;
panose-1:2 11 6 9 2 2 4 3 2 4;}
@font-face
{font-family:NimbusRomNo9L-Regu;
panose-1:0 0 0 0 0 0 0 0 0 0;}
@font-face
{font-family:rtxr;
panose-1:0 0 0 0 0 0 0 0 0 0;}
/* Style Definitions */
p.MsoNormal, li.MsoNormal, div.MsoNormal
{margin:0in;
margin-bottom:.0001pt;
font-size:11.0pt;
font-family:"Calibri","sans-serif";}
a:link, span.MsoHyperlink
{mso-style-priority:99;
color:blue;
text-decoration:underline;}
a:visited, span.MsoHyperlinkFollowed
{mso-style-priority:99;
color:purple;
text-decoration:underline;}
span.EmailStyle17
{mso-style-type:personal-compose;
font-family:"Calibri","sans-serif";
color:windowtext;}
.MsoChpDefault
{mso-style-type:export-only;}
@page WordSection1
{size:8.5in 11.0in;
margin:1.0in 1.0in 1.0in 1.0in;}
div.WordSection1
{page:WordSection1;}
--></style><!--[if gte mso 9]><xml>
<o:shapedefaults v:ext="edit" spidmax="1026" />
</xml><![endif]--><!--[if gte mso 9]><xml>
<o:shapelayout v:ext="edit">
<o:idmap v:ext="edit" data="1" />
</o:shapelayout></xml><![endif]--></head><body lang=EN-US link=blue vlink=purple><div class=WordSection1><p class=MsoNormal>********** Best Viewed in HTML – Apologies for cross-postings **********<o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:14.0pt;font-family:NimbusRomNo9L-Regu'>Postdoctoral Research Opportunity in Developing Adaptive Models that Operate in Non-stationary Environments<o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>Christopher Myers, PhD – Performance & Learning Models team, Air Force Research Laboratory<o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:14.0pt;font-family:NimbusRomNo9L-Regu'><o:p> </o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>I am conducting research that uses machine learning and control theory techniques to model human performance and decision making within dynamic, non-stationary environments. The work involves both human experiments and computational modeling to help explain how humans adapt to changes in dynamic, non-stationary, individual and collaborative task environments. I am looking for a postdoctoral research associate interested in developing cognitively bounded optimal models of visual search, multitasking, and dyadic collaboration. The ideal candidate will have a background in machine learning, cognitive science</span><span style='font-size:10.0pt;font-family:rtxr'>/</span><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>cognitive psychology</span><span style='font-size:10.0pt;font-family:rtxr'>/</span><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>mathematical psychology, and</span><span style='font-size:10.0pt;font-family:rtxr'>/</span><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>or control theory, and will have programming experience with R and</span><span style='font-size:10.0pt;font-family:rtxr'>/</span><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>or Python. Candidates must be a U.S. citizen or permanent resident.<o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'><o:p> </o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>The selected postdoctoral candidate will work with me in the Air Force Research Laboratory’s Performance & Learning Models team located at Wright-Patterson Air Force Base in Dayton, Ohio. AFRL’s PALM team provides a world-class environment for pursuing the application of computational modeling methods to explaining human behavior. The PALM team’s research is focused on both basic and applied cognitive science research questions. The goal is to develop psychologically valid “replicates” of human cognition that can be used to improve the e</span><span style='font-size:10.0pt;font-family:rtxr'>ff</span><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>ectiveness and efficiency of human training (e.g., as synthetic teammates, tutors, or training analysis tools). To achieve these objectives, substantial research is required to understand the components of cognition and how they combine to enable interaction in complex, dynamic environments. Current projects are aimed at understanding topics such as (1) human spatial information processing, (2) changes in cognitive performance resulting from fluctuations in alertness, (3) strategic adaptation to dynamic, non-stationary, complex and persistent environments, & (4) developing technologies that can allow for the creation of computational cognitive models of increased scale (that explain more behaviors within a single system). We utilize a variety of research methodologies, including traditional empirical psychological research, eye tracking, and computational modeling.<o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'><o:p> </o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>If you are interested in pursuing this line of work as a postdoctoral research associate, please contact me as soon as possible at:<o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'><a href="mailto:Christopher.Myers.29@us.af.mil">Christopher.Myers.29@us.af.mil</a><o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'><o:p> </o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>Cheers,<o:p></o:p></span></p><p class=MsoNormal style='text-autospace:none'><span style='font-size:10.0pt;font-family:NimbusRomNo9L-Regu'>Chris</span><o:p></o:p></p><p class=MsoNormal><o:p> </o:p></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>CHRISTOPHER MYERS, PhD<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>Research Psychologist<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>Performance & Learning Models Team<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>Cognitive Models & Agents Branch (RHAC)<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>711 Human Performance Wing<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>2620 Q Street, Bldg 852<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>Wright Patterson AFB OH 45433<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'><o:p> </o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>E: christopher.myers.29 [at] us.af.mil<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>O: 937-938-4059<o:p></o:p></span></p><p class=MsoNormal><span style='font-size:10.5pt;font-family:Consolas'>C: 518-961-6868<o:p></o:p></span></p><p class=MsoNormal><o:p> </o:p></p></div></body></html>