The Department of Statistics, the Department of Electrical Engineering, and the Stanford Neurosciences Institute invite applications for a tenure-track appointment at any level in statistical and computational neuroscience.
Applicants are expected to have a doctoral degree in neuroscience, statistics, electrical engineering, physics, computer science, mathematics, or related disciplines. The home department of the chosen candidate is expected to be Statistics or Electrical Engineering, although other departments may be considered depending on the candidate’s area of research and teaching plan.
The successful candidate will be expected to contribute creatively and in depth to statistical, computational or theoretical approaches to advance the field of neuroscience through both research and teaching. We are open to candidates working in a range of areas including theoretical or applied statistics, applied mathematics, algorithms, optimization, machine learning, data analysis, modeling, information theory, signal processing, and networks. Ideal candidates will demonstrate strong communication and leadership skills, and will be able to actively contribute to our rapidly growing institute as well as their home department.
Applicants should submit a letter of application, curriculum vitae, a statement of research and teaching interests, graduate transcripts, not more than one preprint/reprint, and arrange for three letters of recommendation to be submitted. All materials should be submitted online at https://academicjobsonline.org/ajo/jobs/9339.
Applications must be received by November 1, 2017, to be guaranteed consideration.
Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from others who would bring additional dimensions to the University’s research, teaching and clinical missions.