We are seeking a talented inventive result-driven scientist with an interest in biological image analysis. Experience in facial recognition or related machine vision coding an advantage. The study involves preclinical testing of novel therapies to treat post-menopausal hot flush symptoms in an advanced animal model. The brain selective estrogen being tested is hypothesized to reduce the thermal flush events that occur post-menopausal, without any of the current systemic estrogen therapy side effects on other body organs. The project will involve long term skin temperature monitoring non-invasively via infrared cameras with images collected continuously for months. The first research activity will involve automation of data analysis of images (value of skin temperature, length of elevation, frequency, day-light associations etc., and the effect of brain selective estrogen on skin temperature). The goal to develop high throughput machine vision detection of thermal face hot flush events.
The secondary line of research involves mechanistic studies aimed at better understanding the mechanism of hot flush and the action of estrogen therapy. These studies will involve molecular biological (RT-PCR, in situ hybridization), immunocytochemical and western blot analysis. A successful postdoc, if not proficient with these approaches, may learn these techniques.
The Principal Investigators are committed to assist the postdoc in her/his career development. We are a team of scientists with diverse backgrounds (anatomy, physiology, molecular biology) and welcome candidates from all races, ethnicities, cultures, genders, and gender identities. Interested applicants should apply online through the University of Maryland, School of Medicine website (https://www.umaryland.edu/jobs/), job ID # 210000DY and include: a cover letter, CV, research statement, and contact information for three references.
The University of Maryland, Baltimore is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law or policy.
Good computer, statistical, and image analysis skill
Matlab or other programming language experience
Experience with facial recognition or machine vision coding
Effective written and oral communication skills
* Organized, self-motivated with a strong work ethic
* Ability to work both independently and in a collaborative team environment
* Prior experience and/or understanding of biochemical and molecular biological assays is a plus, but not required.
Image analysis and computer programming (Matlab or other language)
Proficiency in software for data and statistical analyses
Good scientific writing and communication skills
Candidates should have received their Ph.D. or bachelor's degree in physics, computer science, pharmacology, biochemistry, or cell/molecular biology within the last 2-3 years.
Job: Postdoctoral Fellows
Organization: School of Medicine - Clinical Departments
Job Posting: Apr 19, 2021
Internal Number: 170221
About University of Maryland, Baltimore
The University of Maryland, Baltimore (UMB) is the State's public health, law and human services university devoted to excellence in professional and graduate education, research, patient care, and public service. As a diverse community of outstanding faculty, staff and students, and using state-of-the-art technological support, we educate leaders in health care delivery, biomedical science, global health, social work and the law. We emphasize interdisciplinary education and research in an atmosphere that explicitly values civility, diversity, collaboration, teamwork and accountability. By conducting internationally recognized research to cure disease and to improve the health, social functioning and just treatment of the people we serve, we foster economic development in the City, State, and nation. We are committed to ensuring that the knowledge we generate provides maximum benefit to society and directly enhances our various communities.