Hiring.Camp

Assistant Professor Term

Uofl

·

Today

Location
Health Sciences Center, United States of America
Type
Full-time
Department
Education
Education
PhD
Closing date
Today
Source
Workday

Description

Department:

Location:

Health Sciences Center

Time Type:

Full time

Worker Type:

Regular Term (Fixed Term)

Job Req ID:

R109365

Position Description:

 The Division of Immunotherapy, Department of Surgery at the University of Louisville (UofL) School of Medicine seeks a highly motivated bioinformatician at the Assistant Professor level to join our research program.


Division of Immunotherapy, Department of Surgery:

The Division of Immunotherapy is a highly functioning collaborative research team that has had an exceptional track record of grant funding and high impact publications. Faculty members in the Division also have associate appointment with other departments such as the Department of Microbiology and Immunology to train graduate students. The newly recruited faculty member will have office space in the Clinical Translational Research Building (CTRB) along with the rest of the Division; it is fully equipped for research in molecular and cellular immunology, including live cell imaging, single cell and spatial genomics, conventional flow cytometry, mass cytometry and imaging mass cytometry (IMC), cell sorting facility, and state of the art animal housing with germ-free facilities and whole-animal imaging capability (PET/CT scanner).


Facilities and Research Partners:

The UofL School of Medicine provides an outstanding research environment and the majority of the departmental faculty are also members of either the Center for Predictive Medicine (CPM), Center for Cancer Immunology and Immunotherapy (CCII), or Center for Functional Microbiomics, Inflammation and Pathogenicity (CFMIP). The current position offers a wide range of resources as well as collaborative research opportunities. The state-of-the-art facilities of the Immuno-Oncology program at the Brown Cancer Center include a biorepository for clinical specimen collection, clinical trial office, and the CyTOF and imaging mass cytometry (Functional Immunomics Core) to comprehensively phenotype immune landscape within the tumor microenvironment.


Candidate Requirements:

  • The successful candidate will lead computational analyses of high-dimensional biomedical datasets, including single-cell RNA-seq, single-cell ATAC-seq, spatial transcriptomics/proteomics, CyTOF, bulk RNA-seq, and multi-omics datasets.
  • The candidate is expected to develop collaborative research programs, work closely with immunologists, cancer biologists, clinicians, and computational scientists, and contribute to grant applications, manuscript preparation, and trainee mentorship.
  • The ideal candidate should have strong expertise in R/Python programming, single-cell and spatial data analysis, multi-omics integration, machine learning/statistical modeling, and data visualization. Experience in cancer immunology, immunotherapy, inflammation, or immune profiling is highly desirable.
  • Candidates should hold a PhD or equivalent degree in bioinformatics, computational biology, biostatistics, computer science, genomics, or a related field, with a strong publication record and demonstrated ability to work in interdisciplinary teams.

The position offers a competitive salary and a considerable startup package commensurate with qualifications and experience.


Louisville, with a population of over one million and the home of the Kentucky Derby, was chosen as one of the top 10 places for families by Parenting magazine in 2010 and as the most livable city in America by the US Conference of Mayors in 2012. It offers excellent private and public schools for K-12 education and University of Louisville Health Sciences Center has Schools of Medicine, Dental Medicine, Public Health, and Nursing.


Application Process: Applicants should submit the following documents with the application:

1) a cover letter

2) a summary of present and future research plans

3) curriculum vitae

4) the names/email addresses of three references. 

 

Equal Employment Opportunity

The University of Louisville is an Equal Employment Opportunity employer. The University strives to provide equal employment opportunity on the basis of merit and without unlawful discrimination on the basis of race, sex, age, color, national origin, ethnicity, creed, religion, disability, genetic information, sexual orientation, gender, gender identity or expression, veteran status, marital status, or pregnancy. In accordance with the Rehabilitation Act of 1973 and the Vietnam Era Veteran Readjustment Act of 1974, the University prohibits job discrimination of individuals with disabilities, Vietnam era veterans, qualified special disabled veterans, recently separated veterans, and other protected veterans. The University acknowledges its obligations to ensure affirmative steps are taken to ensure equal employment opportunities for all employees and applicants for employment. It is the policy of the University that no employee or applicant for employment be subject to unlawful discrimination in terms of recruitment, hiring, promotion, contract, contract renewal, tenure, compensation, benefits, and/or working conditions. No employee or applicant for employment is required to endorse or condemn a specific ideology, political viewpoint, or social viewpoint to be eligible for hiring, contract renewal, tenure, or promotion.

Consistent with applicable law, demographic information is collected for aggregate reporting requirements. Demographic information provided through this application is not available to hiring managers/committees and is not considered in hiring or employment decisions.

Assistance and Accommodations

Computers are available for application submission at the Human Resources Department located at 2315 South First Street Walk, Room 02C - Louisville, Kentucky 40292.

If you require assistance or accommodation with our online application process, please contact us by email at [email protected] or by phone 502-852-6258.

Skills

PythonMachine Learning

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