Computational Chemistry Scientist - Adjunct Professor Series
The Department of Obstetrics, Gynecology and Reproductive Sciences is seeking a Computational Chemistry Scientist with a focus on high mass spectrometry and the study of the exposome for a full-time faculty position. The selected candidate will be appointed at the level of Assistant Professor in the Adjunct Professor series depending on qualifications and interests.
Faculty in the Adjunct Professor series are individuals who are predominantly engaged in research or other creative work and who participate in teaching, or individuals who contribute primarily to teaching and have a limited responsibility for research or other creative work; these individuals may be professional practitioners of appropriate distinction. The hired candidate will work with a team of experts in analyzing and developing methods for use in non-targeted analysis (NTA) using high resolutions mass spectrometry (HRMS) and computational workflows to assist in the discovery of underreported or unknown organic contaminants in biological and environmental samples. Candidate must also have computational chemistry and programming skills including ability to work with multiple software tools and programming languages for complex and multidimensional data analysis which can include molecular modeling, molecular dynamics simulations, and other data analysis and machine learning. This work will also support human exposure and epidemiological studies that aim to understand the role of environmental exposures in the development of disease. Appointees with titles in this series also engage in University and public service consistent with their assignments.
Qualifications:
- PhD in Environmental Chemistry, Analytical Chemistry, Computational Chemistry, Cheminformatics, Mass Spectrometry, Bioinformatics, or closely related fields with expertise in analytic chemistry methods and environmental health.
- Postdoctoral experience in NTA and HRMS with a focus on environmental chemical exposure and bioinformatics methods including machine learning techniques.
- Extensive experience with analytical chemistry and specifically with HRMS
- Strong programming skills with Python, R, and C/C++
- Extensive experience with data analysis and machine learning with libraries such as TensorFlow and PyTorch.
- Experience in molecular modeling and molecular dynamics.
- Demonstrated ability to collaborate with scientist from difference disciplines, such as biochemistry, environmental science, or toxicological science, to address complete research questions.
Preferred/Desirable Qualifications:
- Experience with grant applications and demonstrated ability to receive funding to support scientific research.
The posted UC salary scales set the minimum pay determined by rank and step at appointment. See Table 5. The minimum base salary range for this position is $121,100-$158,000. This position includes membership in the health sciences compensation plan which provides for eligibility for additional compensation. UCSF Obstetrics, Gynecology & Reproductive Sciences has a total salary plan that uses National benchmarking standards to set salaries by subspecialty.
Please apply online at https://aprecruit.ucsf.edu/JPF05124 with a cover letter, CV, statement of research, statement of contributions to diversity, and contact information for three references. Applicant materials must list current and/or pending qualifications upon submission. The selected candidate must meet all of the qualifications at the time of appointment. To receive full consideration, please submit all materials prior to the initial review date. However, this position will remain open until filled.