Artificial Intelligence and Machine Learning Lead Scientist (Temporary)
Apply NowCompany: University of Nebraska-Lincoln
Location: Lincoln, NE 68516
Description:
Position Information
Position Information
Working Title
Artificial Intelligence and Machine Learning Lead Scientist (Temporary)
Department
Biochemistry-0831
Requisition Number
S_250026
Posting Open Date
01/15/2025
Application Review Date: (To ensure consideration, please submit all application materials before review date)
02/03/2025
Posting Close Date
Open Until Filled
Yes
Description of Work
At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents the majority of immune cell types. The multi-scale computational model integrates mechanistic molecular and cellular-level models with population whole-body models, utilizing machine learning and distributed computing solutions to solve inter- and cross-scale simulations of communication flow. We aim to create real-time, personalizable, and predictive technology.
As the Artificial Intelligence and Machine Learning Lead Scientist, you will:
Temporary employees may be appointed for a period of up to two years. Those appointed for more than six months are eligible for benefits from the beginning of the appointment, provided the position is half-time (.50FTE) or greater. Those appointed for six months or less are not eligible for benefits. Benefits for eligible temporary employees include the following: health, dental, vision and life insurance.
The University of Nebraska-Lincoln seeks to attract and retain a high performing and collaborative workforce. UNL is committed to providing a work environment and culture that fosters personal and professional success where every person and every interaction matters. The University is proud to be one of Nebraska's preferred and largest employers where individuals are able to participate and contribute to their full potential.
As an EO/AA employer, qualified applicants are considered for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See: http://www.unl.edu/equity/notice-nondiscrimination
Minimum Required Qualifications
Preferred Qualifications
Pre-Placement Driving Record Review Required
No
Physical Required
No
Commercial Driver's License (CDL) required. Subject to DOT approved pre-employment & random testing for alcohol and controlled substances.
No
Criminal History Background Check Required
Yes
Posted Salary
Salary commensurate with education and experience.
How to Apply
Click on "Apply for this Job". You will then either create an application or edit your current application that is on file. You will be required to attach your curriculum vitae, cover letter and list of professional references as three (3) separate documents in MS Word or PDF format.
For questions or accommodations related to this position contact
Niveen Dineh
ndineh2@unl.edu
402-472-4545
Job Category (old)
Managerial/Professional
Job Type
Full-Time Temporary
Alternate Work Schedule (if other than 8-5)
Work Location (City, State)
Lincoln, NE
Position funded by grant or other form of temporary funding?
Yes
If Temporary, indicate end date
Planned Hire Date:
As soon as possible.
Appointment End Date
Position Information
Working Title
Artificial Intelligence and Machine Learning Lead Scientist (Temporary)
Department
Biochemistry-0831
Requisition Number
S_250026
Posting Open Date
01/15/2025
Application Review Date: (To ensure consideration, please submit all application materials before review date)
02/03/2025
Posting Close Date
Open Until Filled
Yes
Description of Work
At the Digital Twin Innovation Hub, we are developing infrastructure for the construction, simulation, analysis, and visualization of a human immune system model that represents the majority of immune cell types. The multi-scale computational model integrates mechanistic molecular and cellular-level models with population whole-body models, utilizing machine learning and distributed computing solutions to solve inter- and cross-scale simulations of communication flow. We aim to create real-time, personalizable, and predictive technology.
As the Artificial Intelligence and Machine Learning Lead Scientist, you will:
- Lead the development and execution of multiple AI/ML projects related to multi-scale, multi-cellular immune system modeling.
- Develop, execute, and implement AI/ML infrastructure to simulate the human immune system, diseases, and drug interactions.
- Collaborate with cross-functional teams, including immunologists, biologists, computational biologists, clinicians, data scientists, and software engineers to enhance the understanding of the human immune system and underlying immune-related conditions and treatments.
- Be responsible for project management of a team of contractors and staff working on the project, providing advanced scientific expertise to aid in problem solving to ensure that project timelines are met and goals achieved.
Temporary employees may be appointed for a period of up to two years. Those appointed for more than six months are eligible for benefits from the beginning of the appointment, provided the position is half-time (.50FTE) or greater. Those appointed for six months or less are not eligible for benefits. Benefits for eligible temporary employees include the following: health, dental, vision and life insurance.
The University of Nebraska-Lincoln seeks to attract and retain a high performing and collaborative workforce. UNL is committed to providing a work environment and culture that fosters personal and professional success where every person and every interaction matters. The University is proud to be one of Nebraska's preferred and largest employers where individuals are able to participate and contribute to their full potential.
As an EO/AA employer, qualified applicants are considered for employment without regard to race, color, ethnicity, national origin, sex, pregnancy, sexual orientation, gender identity, religion, disability, age, genetic information, veteran status, marital status, and/or political affiliation. See: http://www.unl.edu/equity/notice-nondiscrimination
Minimum Required Qualifications
- Master's degree in Artificial Intelligence, Machine Learning, Computer Science (with focus on AI/ML), Data Science, Software Engineering, or related field.
- Six (6) years of experience with real-world AI/ML projects, including designing algorithms, building models, and deploying systems. A PhD in a related field may substitute for two years of the required experience.
- Experience must include at least three (3) years of managing projects and supervising staff members in diverse disciplines.
- Experience training scientists, with the ability to communicate complex concepts and insights to non-expert stakeholders.
- Proficiency in computational tools and software used in AI/ML (e.g.,Python, C++, Julia).
- Strong analytical and problem-solving skills.
Preferred Qualifications
Pre-Placement Driving Record Review Required
No
Physical Required
No
Commercial Driver's License (CDL) required. Subject to DOT approved pre-employment & random testing for alcohol and controlled substances.
No
Criminal History Background Check Required
Yes
Posted Salary
Salary commensurate with education and experience.
How to Apply
Click on "Apply for this Job". You will then either create an application or edit your current application that is on file. You will be required to attach your curriculum vitae, cover letter and list of professional references as three (3) separate documents in MS Word or PDF format.
For questions or accommodations related to this position contact
Niveen Dineh
ndineh2@unl.edu
402-472-4545
Job Category (old)
Managerial/Professional
Job Type
Full-Time Temporary
Alternate Work Schedule (if other than 8-5)
Work Location (City, State)
Lincoln, NE
Position funded by grant or other form of temporary funding?
Yes
If Temporary, indicate end date
Planned Hire Date:
As soon as possible.
Appointment End Date