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<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>With
apologies and respect to our valued colleagues of other nationalities, only
U.S. citizens and permanent legal residents of the United States are eligible
for these positions.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>We
have a variety of research positions available for talented cognitive,
computational, and computer scientists interested in working with the U.S. Air
Force Research Laboratory's Performance and Learning Models (PALM) Team on
basic and applied cognitive science research. Full-time, paid positions range
from undergraduate and graduate-level internships and research assistantships,
to post-doctoral research appointments, to visiting faculty appointments.
Salaries are commensurate with experience. <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>The
PALM research portfolio continues to expand and evolve. We use a combination
of empirical human-subjects studies and formal, rigorous, computational and
mathematical modeling and simulation methods to understand, replicate, and
predict human performance and learning, and to create new cognitive
science-based technology options. Currently there are research efforts
underway in all of the following areas (with associated PIs):<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><b><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Basic
research:<o:p></o:p></span></b></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- large scale cognitive modeling (Scott Douglass)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- representations and processes of spatial visualization (Glenn Gunzelmann)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- modeling the relationships between alertness and cognitive processes (Glenn
Gunzelmann)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- persistent, generative, situated agents (Christopher Myers)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><b><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Applied
research:<o:p></o:p></span></b></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- natural language comprehension and generation (Jerry Ball)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- robust decision making in integrated human-machine systems (Kevin Gluck)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- model exploration and optimization using distributed and high performance
computing (Jack Harris)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- mathematical models for performance prediction and prescription (Tiffany
Jastrzembski)<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Brief
elaborations of each area can be found below. <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><b><span style='font-size:12.0pt;font-family:"Arial","sans-serif"'>Anyone
interested in working with us on one or more of the research efforts listed
above is encouraged to contact the PI for that particular research area as soon
as possible. Email addresses are first.last<at>mesa.afmc.af.mil<o:p></o:p></span></b></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Natural
language comprehension and generation (Jerry Ball)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>The
focus of the natural language research is development of computational
cognitive models which are both functional and cognitively plausible. There may
be short-term costs associated with adoption of cognitive constraints, but we
expect, and have to some extent already realized, longer-term benefits. We
focus on communication via text messaging, avoiding complex challenges of
speech recognition, but make no assumptions about the grammatical quality of
messages and put no arbitrary limits on their linguistic range. Our current
project, the Synthetic Teammate, is aimed at development of a cognitive agent
capable of functioning as the pilot of a simulated UAV. The cognitive agent
interacts with two teammates—a navigator, and a photographer—in
order to take pictures of ground targets over the course of a simulated 40
minute reconnaissance mission. Lightweight agent versions of the navigator and
photographer currently support development, but the cognitive agent will
eventually interact with human teammates in an empirical study. <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Large
scale cognitive modeling (Scott Douglass)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Explores
how paradigms in software engineering called "meta-modeling" and
"model-integrated computing" can be used to produce domain-specific
modeling languages tailored to the specification and integration needs of
cognitive modelers. These new formalisms will help cognitive modelers increase
the scale of their efforts by allowing them to specify self-modifying models at
high levels of abstraction. These new formalisms will share a foundation in
general systems theory and will therefore help their users: (a) compose and
compare models; and (b) integrate models into task environments and simulations
that subscribe to the same formal foundation. This research reciprocates value
back to software engineering by demonstrating how specifications of cognitive
processes can be formally captured and exploited during the design of
human/machine systems.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Representations
and processes of spatial visualization (Glenn Gunzelmann)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Human
spatial competence is applied ubiquitously as individuals encode information
about the location of objects in the world, plan routes and navigate through
the environment, reason about spatial relationships, or make decisions in
environments that are rich with spatial information. Despite the criticality of
spatial information processing in human cognitive functioning, detailed
mechanistic theories that can be used to explain and predict behavior are
lacking. Our research in this area is targeted at producing a mechanistic,
quantitative theory of human spatial competence, focused on representing and
processing visuospatial knowledge. This research involves rigorous empirical
data collection, to understand human performance in this area and to support
validation of quantitative theoretical accounts instantiated as mathematical
and computational models.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Modeling
the relationships between alertness and cognitive processes (Glenn Gunzelmann)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Understanding
the functioning of the human cognitive system is as important as understanding
the human physiological system in operational environments. As an example,
research on fatigue has uncovered neurophysiological changes in the human brain
resulting from sleep loss, circadian desynchrony, or time on task. In addition,
corresponding deficits in human performance on a variety of tasks have been
documented in the empirical literature. What is unknown, however, are the
mechanisms through which physiological changes impact cognitive performance.
This line of research is aimed at understanding how cognitive processing
changes as a result of fatigue, bridging the gap between mathematical models
that capture the dynamics of overall change in neurobehavior performance and in
situ performance on particular tasks.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Robust
decision making in integrated human-machine systems (Kevin Gluck)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>It
is increasingly clear that the traditional boundaries between human and machine
are disappearing. The future vision of integrated human-machine decision
systems is already upon us. Hence, there is escalating pressure on AFRL
researchers to better understand the basic science of mixed human –
machine decision making, and make use of this science to develop increasingly
robust, automated knowledge-extraction tools and intelligent machine-based
decision aids that optimize, speed up, and adaptively adjust inference,
prediction, and decision processes. This is a new-start research area in which
we are interested in new models and methods for assuring high quality decision
processes and outcomes, especially in complex and uncertain dynamic
environments. <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Model
exploration and optimization using distributed and high performance computing
(Jack Harris)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Computational
complexity grows quickly with increases in the granularity of models, the
fidelity of the models’ operating environment, and the time scales across
which these models are used in simulations. We must find ways to deal with the
computational demands of large-scale basic and applied cognitive modeling. One
approach is to acquire more computational horsepower, such as through high
performance computing (HPC) clusters, volunteer computing, or cloud computing.
Another approach is to reduce the size of the required computational space
through predictive analytics and parallelized exploration and optimization
algorithms. Our view is that it is only through the combined use of these
approaches that we can meet our far-term scientific and technological
objectives, both as a research team and as a broader research community.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Mathematical
models for performance prediction and prescription (Tiffany Jastrzembski)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Training
people to stable levels of high performance in specialized skills requires a
great deal of investment in both time and capital, and this is particularly
true in highly complex domains like military operations. Given the length,
complexity, resource limitations, and cost of warfighter training, it is
critical to ensure that the timing and frequency of training events are
tailored to the needs of the learner to maximize learning and performance
effectiveness. This research identifies the mathematical regularities of human
learning and forgetting as a function of the temporal distribution of training
in order to (1) validly, precisely, and quantitatively predict future levels of
learner performance, and to (2) prescribe more optimal training schedules to
enhance retention, achieve more effective learning, and streamline training to
the needs of the individual.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><u><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Persistent,
generative, situated agents (Christopher Myers)<o:p></o:p></span></u></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>The
typical approach to computational cognitive modeling is to isolate a process of
interest and capture enough detail within the model to account for a set of
data obtained from humans performing within a particular task environment. The
promise of this approach is that veridical models of cognitive processes will
eventually be integrated to produce more complex processes. While this approach
has proven beneficial to isolating, studying, and understanding arguably
distinct cognitive processes, the resulting models are typically brittle,
engineered, short-lived and tailored to specific experimental psychology
paradigms. These characteristics are limitations to the development of models
which require persisting over long periods of time and generating their own
knowledge. This research is focused on identifying, developing, and integrating
process models of cognitive capacities to enable persistent and generative
models.<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>-------------------------------------------------------
<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>KEVIN
GLUCK, PhD <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Senior
Research Psychologist <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>S&T
Advisor, Cognitive Models and Agents Branch <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Air
Force Research Laboratory <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>6030
S. Kent St <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>Mesa,
AZ 85212-6061 <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>P:
480-988-6561 x-677; DSN 474-6677 <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>F: 480-988-2230;
DSN 474-6688 <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>C:
480-229-4569 <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>"The
true line is not between 'hard' natural science and 'soft' social sciences, but
between precise science limited to highly abstract and simple phenomena in the
laboratory and inexact science and technology dealing with complex problems in
the real world."<o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'>
- Herb Simon, Models of My Life <o:p></o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
<p class=MsoPlainText><span style='font-size:10.0pt;font-family:"Arial","sans-serif"'><o:p> </o:p></span></p>
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