Machine Learning Specialist (Zylka Lab)

Job description

Posting Details

Position TypeTemporary Staff (SHRA)Job TitleMachine Learning Specialist (Zylka Lab)Department NameCell Biology and Physiology - 422001Vacancy IDS016967Position Posting CategoryResearch ProfessionalsHiring Range$20-26/hourFull-time/Part-timeFull TimeIf part-time, how many hours per week?Work ScheduleProposed Start DateEstimated Duration of Appointment6 months not to exceed 11 monthsPosting Open Date10/02/2020Posting Close Date10/23/2020Description of Work

The Department of Cell Biology and Physiology is a basic science department in the School of Medicine and engages in a broad range of teaching and research activities. Faculty in the Department conduct research on a variety of problems ranging from the study of nervous system function to the control of blood pressure. It is also strong in renal, endocrine, respiratory, cardiovascular and neurophysiology. Faculty in this department also interacts with clinical departments within the School of Medicine. The department’s breadth of research interests allows us to offer students a unique exposure to physiology at the molecular, cellular and organ levels. Active interaction occurs with other basic science departments at the University as well as collaboration with scientists at nearby Duke University and Research Triangle Park.

Primary purpose of this position:
The primary purpose of this temporary Machine Learning specialist position is to develop a machine learning algorithm to quantify pain from mouse facial expressions, body posture, and motion. Will be expected to work with a team of neuroscientists, data scientists, and programmers to train and test deep learning architectures (CNNs, RNNs, etc), with the ultimate goal of integrating a fully trained and accurate model into a web-based platform as well as a mobile app.

Duties and Responsibilities:
80% Procedures:
The employee will work under the supervision of the P.I. and/or senior research staff to complete the following experimental procedures:
1) Develop deep-learning/machine learning approaches for insight and analysis about mouse behavior from video data.
2) Make it easy to get high quality, automated, results without expert intervention. Build scalable products and reusable libraries in Python and/or C++, taking advantage of TensorFlow, PyTorch, and other tool stacks as appropriate.
3) Interact cross-functionally: work with people across the team to find creative solutions and deliver them.
4) Skilled at data visualization and presentation.

20% Interpretation or evaluation of data

This position will report results directly to the P.I., the Co-PI and/or senior research staff on a daily basis. This individual must have the ability to solve routine problems and make routine decisions but must consult with the PI or supervisor for guidance.

Education and Experience

Bachelor’s degree in Computer Science, Information Science, Engineering, or a related discipline. Experience with Computer Vision and Deep Learning architectures (CNNs, RNNs, etc), programming skills with proficiency in Python, Java, and/or C++.

Special Physical and Mental RequirementsEqual Opportunity Employer Statement

The University of North Carolina at Chapel Hill is an equal opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to age, color, disability, gender, gender expression, gender identity, genetic information, race, national origin, religion, sex, sexual orientation, or status as a protected veteran.

Stimulus/ARRA FundedNoSpecial Instructions Temporary Employment Policies

Temporary Employment Policies

Quick Link of Human Resources Contact Information

If you experience any problems accessing the system or have questions about the application process, please contact the Office of Human Resources at (919) 843-2300 or send an email to [email protected]

Please note: The Office of Human Resources will not be able to provide specific updates regarding position or application status.

Optional and Required DocumentsRequired Documents
  1. Curriculum Vitae / Resume
  2. Cover Letter
  3. List of References
Optional Documents
    Supplemental Questions

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      Job No:
      Posted: 10/16/2020
      Application Due: 10/23/2020
      Work Type: