Remote Senior Scientist - Cognitive Psychology & ML

University of Arizona College of Medicine - Phoenix; Tucson (AZ); Hybrid; USD 59,000 - 89,000; Part time

Benefits offered by this job

Full benefits

Tuition reduction for employee and affir

Job summary

University of Arizona College of Science invites applications for a Part Time Senior Scientist in Psychology to support the Naiadel Lab with computational and neurophysiological research.

The role involves developing software and infrastructure for cognitive studies in lab and online settings, integrating EEG and eye-tracking, and building reproducible processing pipelines with ML methods.

Qualifications

• Bachelor's degree in engineering, computer science, cognitive science, psychology, neuroscience, or related field.
• Minimum of five years of professional or research experience in cognitive/behavioral research with relevant tech.
• Experience developing, implementing, or maintaining experimental software and research infrastructure.

Responsibilities

• Develop, test, and maintain specialized research software and experimental infrastructure for cognitive/behavioral studies.
• Integrate EEG, eye-tracking and other physiological measures with experimental software and data workflows.
• Develop reproducible analytical pipelines for processing neurocognitive data and apply machine learning methods.
• Configure and maintain research computing resources and backend data workflows for online studies.

Skills

Cognitive/behavioral research methods

Quantitative data analysis

Scientific programming

Python

C++

Education

Bachelor's degree in a related field

Tools

TestEnv

jsPsych

Python

C++

Job description

University of Arizona College of Science invites applications for a Part Time Senior Scientist in Psychology to support the Naiadel Lab with computational and neurophysiological research.

The role involves developing software and infrastructure for cognitive studies in lab and online settings, integrating EEG and eye-tracking, and building reproducible processing pipelines with ML methods.