Post-doctoral Position (24 months)

University of Michigan

Predicting Individual Outcomes for Rapid Interventions

(PRIORI)

Context: Bipolar disorder (BP) is a common and severe psychiatric illness characterized by

pathological swings of mania and depression and is associated with devastating personal,

social, and vocational consequences (suicide occurs in up to 20% of cases [1]). Bipolar disorder

is among the leading causes of disability worldwide [2]. The cost in the United States alone was

estimated at $45 billion annually [3]. These economic and human costs, along with the rapidly

increasing price of health care provide the impetus for a major paradigm shift in health care

service delivery, namely to monitor and prioritize care with a focus on prevention. In this project

we focus on how to using mobile health technologies to automatically track mood variation in

populations with BP. We have a large collection of ecologically recorded smartphone calls, now

numbering over 22,000, and are investigating how to characterize mood in these data.

Overview of Position: The candidate will have the opportunity to analyze spoken data from

individuals with bipolar disorder, collected over the period of six months to a year. Our goal is to

predict mood states from natural speech. Significant opportunities exist in machine learning,

speech processing, user personalization, and health-centered computing. We are currently

processing our massive ecologically valid set of speech data from individuals with bipolar

disorder to uncover the acoustic characteristics of speech that will allow us to intuit mood state

(manic, depressed, euthymic) and mood state change. The candidate will interact with an

established team including experts in affective processing (Emily Mower Provost), reinforcement

learning (Satinder Singh), and psychiatry (Melvin McInnis). We are seeking postdoctoral

candidates with experience in machine learning, speech processing , and human-centered

computing.

Keywords: Machine learning, speech processing, and human-centered computing.

Prerequisite: PhD degree in computer science, signal processing, or machine learning. Strong

knowledge in programming languages and database management are desired.

To apply: Interested applicants should email their CV, a cover letter outlining their experience

and research background, two references, and their two-three most relevant papers to Emily

Mower Provost (emilykmp@umich.edu).

References:

[1] Frederick K Goodwin and Kay Redfield Jamison, Manic-depressive illness: bipolar disorders

and recurrent depression, vol. 1, Oxford University Press, 2007.

[2] Alan D Lopez, Colin D Mathers, Majid Ezzati, Dean T Jamison, and Christopher JL Murray,

“Global and regional burden of disease and risk factors, 2001: systematic analysis of population

health data,” The Lancet, vol. 367, no. 9524, pp. 1747–1757, 2006.

[3] Leah S Kleinman, Ana Lowin, Emuella Flood, Gian Gandhi, Eric Edgell, and Dennis A

Revicki, “Costs of bipolar disorder,” Pharmacoeconomics, vol. 21, no. 9, pp. 601–622, 2003.