Temporary Research Data Analyst III

University of Louisville; Louisville (KY); On-site; USD 40,000 - 70,000; Full time

Job summary

An established industry player is looking for a dedicated researcher to join its Bioengineering Department. This temporary role focuses on analyzing biomedical data related to cancer and lung diseases, utilizing advanced computational analysis and modeling techniques. You will develop software platforms that leverage machine learning and statistical methods, while also processing patient tissue samples for research. The position offers the chance to collaborate with students and clinical researchers, enhancing your skills in a dynamic environment. If you're passionate about making a difference in healthcare through innovative research, this opportunity is for you.

Qualifications

• 4+ years of experience in computational analysis and mathematical modeling.
• Ability to work autonomously and in teams with researchers.

Responsibilities

• Analyze biomedical datasets to predict disease progression.
• Develop software platforms using machine learning techniques.
• Visualize results and write manuscripts for research presentation.

Skills

Computational Analysis

Mathematical Modeling

Machine Learning

Statistical Techniques

Communication Skills

Autonomy

Risk Identification

Education

Bachelor's Degree in Bioengineering

Equivalent Combination of Training and Experience

Tools

Python

Matlab

R Programming

Job description

Department:

Location:
Belknap Campus
Time Type:
Full time
Worker Type:
Temporary (Fixed Term)
Job Req ID:
R106741
Minimum Requirements:
Four (4) years' experience or equivalent combination of training and experience.
Position Description:

The Department of Bioengineering is seeking applicants interested in the analysis of biomedical data, with research focusing on cancer and lung diseases. Have a proven track record of computational analysis and mathematical modeling applied to biological phenomena. This is a temporary position that will serve to study and analyze biological data for research purposes.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Analyze biomedical datasets to predict disease progression and treatment response
• Develop software platforms using machine learning and statistical techniques
• Process patient tissue samples for analysis
• Visualize results, manuscript writing, and presentation to other researchers.

PREFERRED QUALIFICATIONS

• Bachelor's degree in Bioengineering or Biomedical Engineering from an accredited college or university, or equivalent combination of training and experience
• Ability to interface with students, researchers, and clinical collaborators
• Excellent written and verbal communication skills
• Must be able to work autonomously or as part of a team of researchers
• Ability to identify risks and issues and make recommendations regarding scope, schedule, and resources
• At least 1 year experience as a researcher involved with machine learning and computational simulation
• Experience with patient tissue sample processing for analysis
• Previous experience in bioengineering academic research
• Knowledge of Python, Matlab, and/or R programming
• Knowledge of partial differential equations and numerical solvers

Compensation will be commensurate to candidate experience.

Equal Employment Opportunity

The University of Louisville is an equal opportunity, affirmative action employer, and is committed to providing employment opportunities to all qualified applicants without regard to race, sex, age, color, national origin, ethnicity, creed, religion, disability, genetic information, sexual orientation, gender, gender identity and expression, marital status, pregnancy, or veteran status. If you are unable to use our online application process due to an impairment or disability, please contact the Employment team at [e-mail] or 502.852.6258.

Assistance and Accommodations

Computers are available for application submission at the Human Resources Department located at 215 Central Avenue, Ste 205 - Louisville, Kentucky 40208.

If you require assistance or accommodation with our online application process, please contact us by email at [e-mail] or by phone [phone].