Link copied to clipboard!
Back to Jobs
Assistant Professor-Tenure Track-Expertise in Cancer Immunotherapy and Computational Immunology-Pathology and Laboratory Medicine
Location: Philadelphia, PA
Open Date: May 14, 2025
Deadline: May 14, 2027 at 11:59 PM Eastern Time
The Department of Pathology and Laboratory Medicine at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for an Assistant Professor position in the tenure track. Expertise is required in the specific area of Laboratory Medicine, Cancer Immunotherapy, and Computational Immunology. Applicants must have an M.D. or M.D./Ph.D. or equivalent degree. American Board of Pathology, CP-only or AP/CP.
Teaching responsibilities may include medical and graduate students, residents, and fellows, particularly in the areas of immunology, cancer biology, and computational methods.
Clinical responsibilities may include participation in Laboratory Medicine Division consultation responsibilities, specifically the protein electrophoresis service through the Hospital of the University of Pennsylvania.
Research or scholarship responsibilities may include development of an independent research program (as PI) in the area of cancer immunotherapy and computational immunology.
Qualifications
Application Instructions
To apply, visit https://apply.interfolio.com/166951
Equal Employment Opportunity Statement
The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.
Copyright ©2025 Jobelephant.com Inc. All rights reserved.
Posted by the FREE value-added recruitment advertising agency jeid-a62fce95cf89d845a22d242f6b0a496f
Assistant Professor-Tenure Track-Expertise in Cancer at InsideHigherEd
InsideHigherEd
Philadelphia, Pennsylvania
Education
Posted 0 days ago
Job Description
Assistant Professor-Tenure Track-Expertise in Cancer Immunotherapy and Computational Immunology-Pathology and Laboratory Medicine
Location: Philadelphia, PA
Open Date: May 14, 2025
Deadline: May 14, 2027 at 11:59 PM Eastern Time
The Department of Pathology and Laboratory Medicine at the Perelman School of Medicine at the University of Pennsylvania seeks candidates for an Assistant Professor position in the tenure track. Expertise is required in the specific area of Laboratory Medicine, Cancer Immunotherapy, and Computational Immunology. Applicants must have an M.D. or M.D./Ph.D. or equivalent degree. American Board of Pathology, CP-only or AP/CP.
Teaching responsibilities may include medical and graduate students, residents, and fellows, particularly in the areas of immunology, cancer biology, and computational methods.
Clinical responsibilities may include participation in Laboratory Medicine Division consultation responsibilities, specifically the protein electrophoresis service through the Hospital of the University of Pennsylvania.
Research or scholarship responsibilities may include development of an independent research program (as PI) in the area of cancer immunotherapy and computational immunology.
Qualifications
Application Instructions
To apply, visit https://apply.interfolio.com/166951
Equal Employment Opportunity Statement
The University of Pennsylvania is an equal opportunity employer. Candidates are considered for employment without regard to race, color, sex, sexual orientation, religion, creed, national origin (including shared ancestry or ethnic characteristics), citizenship status, age, disability, veteran status or any class protected under applicable federal, state, or local law.
Copyright ©2025 Jobelephant.com Inc. All rights reserved.
Posted by the FREE value-added recruitment advertising agency jeid-a62fce95cf89d845a22d242f6b0a496f
Resume Suggestions
Highlight relevant experience and skills that match the job requirements to demonstrate your qualifications.
Quantify your achievements with specific metrics and results whenever possible to show impact.
Emphasize your proficiency in relevant technologies and tools mentioned in the job description.
Showcase your communication and collaboration skills through examples of successful projects and teamwork.