Job Description
Organization
H0070 Electrical Engineering
Description
Supervises and coordinates the activities of personnel engaged in research and experimental testing. Maintains lab operations. May investigate complaints regarding lab services, equipment, and/or capabilities. Possesses, understands, and applies a comprehensive knowledge in area of specialization. Understands and uses effective management techniques.
Duties:
- Manages the budgets and operations of two or more research laboratories.
- Assigns, checks, and monitors assignments of lab personnel.
- Oversees and participates in the creation of annual budgets.
- Identifies funding sources and applies for grants, as appropriate.
- Estimates personnel needs to obtain lab and research objectives.
- Conducts personnel evaluations, recommends hiring and terminations, and performs other management functions.
Supervision: Operates with considerable latitude for unreviewed action. Reviews and evaluates the effectiveness of personnel.
About Us: Houston Learning Algorithms Laboratory focuses on cutting-edge AI technology for healthcare and medical applications. Our team is composed of passionate individuals who thrive on collaboration and creativity, and we are seeking a Research Lab Manager to oversee our machine learning and healthcare research initiatives. Will work under the supervision of Dr. Hien V. Nguyen.
We are looking for a talented Research Lab Manager with expertise in machine learning, healthcare applications, and medical imaging to join our dynamic team. In this role, you will be responsible for managing our research lab, coordinating research projects, and ensuring the successful execution of our healthcare-focused machine learning initiatives.
Specific Duties:
- Manage and oversee the daily operations of the research lab.
- Coordinate and lead research projects with a specific focus on healthcare and medical imaging applications.
- Work closely with machine learning researchers and healthcare professionals to ensure project success.
- Utilize big data to extract meaningful insights in the healthcare domain.
- Manage machine learning infrastructure and ensure scalability for healthcare projects.
- Maintain and optimize databases such as GraphQL and MongoDB for healthcare data.
- Stay up-to-date with the latest advancements in machine learning and healthcare.
- Communicate research findings effectively through presentations and reports.
- Foster a collaborative and innovative work environment within the lab.
If you are passionate about machine learning, enjoy working on challenging problems in healthcare, and want to play a pivotal role in advancing our research initiatives, we encourage you to apply.
To apply for this position, please submit your resume and any relevant portfolio or publications.
Qualifications:
Bachelors and 7 years experience
Additional Job Posting Information:
- Department is willing to accept education in lieu of experience.
Preferred Qualifications:
- PhD degree in machine learning, statistical learning, or optimization.
- Minimum of 5 years of industry experience, with a strong focus on healthcare and medical imaging applications.
- Strong proficiency in Python, PyTorch, and TensorFlow.
- Experience with managing and scaling machine learning infrastructure for healthcare.
- Proficiency in databases such as GraphQL and MongoDB, with experience handling healthcare data.
- Exceptional problem-solving skills.
- Excellent communication and teamwork skills.
- A significant research background in machine learning and optimization, demonstrated by publications or projects in healthcare and medical imaging.
Salary: Commensurate with Experience/Education
Required Attachments by Candidate: Curriculum Vitae, Cover Letter/Letter of Application
Employee Status
Job Posting
Job Posting: Jul 29, 2024, 8:15:12 PM
The policy of the University of Houston System and its universities is to ensure equal opportunity in all its educational programs and activities, and all terms and conditions of employment without regard to age, race, color, disability, religion, national origin, ethnicity, military status, genetic information, sex (including gender and pregnancy), sexual orientation, gender identity or status, or gender expression, except where such a distinction is required by law.
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