Senior Research Scholar: Connectomics

the scholar will develop computational methods, software, and data resources to enable original scientific investigations and reproducible analysis. The successful candidate will conduct independent and collaborative studies, and publish resulting scientific findings. The scholar will collaborate with Princeton faculty and external investigators and will seek external funding to advance independent and collaborative connectomics research. Key Responsibilities Conduct Original Research in Computational Connectomics: Formulate and investigate research questions in connectomics, reconstruction and annotation, cell-type organization, comparative connectomics, circuit analysis, and relationships between connectivity and function. Develop new computational approaches where needed to address these questions. Publish and Disseminate Research: Produce original scientific contributions in connectomics. Publish research findings, present results at scientific meetings, and release datasets, software, and analytical resources to the research community. Contribute to Mentoring and Teaching: Co-mentor undergraduate and graduate students, postdoctoral researchers, research staff, and software engineers, in collaboration with faculty. Contribute to workshops, tutorials, and other research training activities. Possibility of teaching or co-teaching undergraduate courses, subject to enrollment, curricular need and applicable University approvals. While teaching, the Senior Research Scholar will carry the additional part-time rank of Lecturer. Seek Funding for New Research Directions: Identify funding opportunities; prepare and submit grant applications, contribute to sponsored research projects, and develop new scientific collaborations and research initiatives. Qualifications Essential Qualifications Ph.D. in computer science/computational neuroscience or a related field. A minimum of ten years of relevant research experience following completion of the Ph.D. Recognized distinction and sustained scholarly achievement in connectomics, computational neuroscience, or a closely related field. Demonstrated record of original and creative research and independent contributions to knowledge. Strong record of peer-reviewed publications demonstrating significant contributions to the field. Demonstrated ability to formulate and pursue an independent program of research. Ability to guide and direct researchers and students participating in programs of research. Substantial experience developing computational methods, research software, or data infrastructure for large-scale neuroscience. Strong scientific communication and collaboration skills. Preferred Qualifications Experience with analyzsing petabyte-scale electron microscopy connectomic data and associated connectivity/annotation meta data. Expertise in large graph algorithms, machine learning, circuit analysis, or comparative connectomics. Experience leading the development and operation of scientific software platforms, databases, or community data resources. Experience integrating and disseminating large scientific datasets. Experience preparing grant applications and managing externally funded research projects. Experience teaching connectomics, computational neuroscience, data analysis, or related subjects. A record of extensive collaboration across laboratories, institutions, or scientific consortia. Demonstrated experience leading interdisciplinary scientific and technical projects. Appointments, to be made at the rank of Senior Research Scholar, with an anticipated start date of July 1, 2027 . This position follows a hybrid work arrangement, with work performed both on the Princeton University campus and remotely. This position is subject to the University's background check policy and review and approval by the Advisory Committee on Appointments and Advancements for Academic Professionals. Application Instructions Interested applicants must submit a cover letter, curriculum vitae, research statement, bibliography and contact information for two references. Equal Employment Opportunity Statement Princeton University is an Equal Opportunity Employer and all qualified applicants will receive consideration for employment without regard to age, race, color, religion, sex, sexual orientation, gender identity or expression, national origin, disability status, protected veteran status, or any other characteristic protected by law. Pay Transparency Disclosure The University considers factors such as (but not limited to) the scope and responsibilities of the position, candidate's qualifications, work experience, education/training, key skills, market, collective bargaining agreements as applicable, and organizational considerations when extending an offer. The posted salary range represents the University's good faith and reasonable estimate for a full-time position; salaries for part-time positions are pro-rated accordingly. The University also offers a comprehensive benefits program to eligible employees. Please see this link for more information. PI287684536