The successful candidate will collaborate with Dr. Sara Bombaci and undergraduate technicians on NSF-funded research to collect and analyze data, publish research on socioeconomic status (SES)-realted biases in citizen science data, and investigate how SES, urban development, and natural environments influence biodiversity across multiple cities.

Remote and in person options available. 

Required Qualifications

• Ph.D. degree in a pertinent biological, physical, or computer science field by start date of position.
• Must have a valid driver’s license or the ability to obtain a driver’s license or access to a licensed driver by the employment start date.

Preferred Qualifications

• Proficiency in statistical methods, especially using spatial statistics to analyze large, complex spatial datasets. This includes skills in handling large datasets, data cleaning, and integration of multiple datasets (e.g., citizen science data from eBird with other reference datasets).
• Record of scholarly publication.
• Experience with social-ecological research in urban settings.
• Experience collaborating with diverse groups including academic faculty, staff, and supervising and mentoring graduate/undergraduate students.
• Demonstrated written and verbal communication skills to convey findings to both scientific and non-scientific audiences.
• Personal and professional commitment to diversity as demonstrated by involvement in teaching, research, outreach, creative activity, service to the profession and/or diversity/inclusion activities.