Staff Scientist

Department
 

BSD OBA - Palmer Lab

About the Department
 

This position requires the expertise of an experienced scientist in both natural scene analysis and computational neuroscience. We are looking for this key person to fill out roles in our current grants on coarse-graining in neural systems as well as predictive computation in the visual system. The research scientist will work independently on at least two major projects, and is expected to produce publishable results.

Job Summary
 

The job develops and implements programs to promote a research project or contributes to the scientific direction of a research resource.

Responsibilities

• Curating and extended our natural motion database.

• Mentoring graduate students on the analysis of retinal population data, in response to synthetic and natural scenes.

• Designing novel naturalistic visual stimuli that mimic the statistics of motion in the natural world, using techniques from statistical physics and applied mathematics.

• Managing an existing collaboration with the group of Olivier Marre at Paris VI university by organizing zoom meetings, analyzing data, working up toy models to develop new stimulus paradigms, and overseeing graduate student progress on these projects.

• Writing and publishing papers on these findings.

• Assisting with generating preliminary data and text for grant proposals.

• Serves as a resource for collecting data and performing analysis. Facilitates and promotes a research project by providing scientific or intellectual information.

• Trains and mentors laboratory personnel.

• Performs other related work as needed.

Minimum Qualifications
 

Education:

Minimum requirements include a PhD in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 5-7 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications

Education:

• Doctorate in computer science or another relevant field or research, such as Applied Mathematics.

Experience:

• Three years postdoctoral experience in neuroscience, particularly in visual processing and information theory.

• Knowledge of and experience with modern computational and machine learning techniques, such as Variational Auto-Encoders, Information Bottleneck approaches in statistical physics.

• Knowledge of the physiology and anatomy of both vertebrate and invertebrate visual systems. 

Application Documents

• Cover Letter (required)

• Resume (required)

• Contact information for at least 2 references (required)

When applying, the document(s) MUST  be uploaded via the My Experience page, in the section titled Application Documents of the application.

Job Family
 

Research

Role Impact
 

Individual Contributor

FLSA Status
 

Exempt

Pay Frequency
 

Monthly

Scheduled Weekly Hours
 

37.5

Benefits Eligible
 

Yes

Drug Test Required
 

No

Health Screen Required
 

No

Motor Vehicle Record Inquiry Required
 

No

Posting Statement
 

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

 

Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

 

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.

 

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

 

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