Healthcare Data & ML Research Assistant

Elevate Clinical; Houston, Northern (TX, KY); Hybrid; USD 40,000 - 60,000; Full time

Job summary

Elevate Clinical Research in Houston, TX seeks a Research Assistant to support healthcare and social assistance research by collecting, processing, and analyzing complex datasets for data-driven studies and experimental protocols.

The role involves collaboration with interdisciplinary teams to design methodologies, including computational and laboratory techniques, and to contribute to development and validation of machine learning models for biomedical data.

Qualifications

• Proficiency in data collection methods and laboratory techniques including gel electrophoresis.
• Experience with programming and data analysis tools such as TensorFlow, NumPy, and SPSS.
• Basic understanding of algorithms, neural networks, and deep learning concepts.
• Strong organizational skills and attention to detail in managing research data.
• Masters degree in health data analytics or computational biology (preferred).

Responsibilities

• Conduct comprehensive data collection through field research and laboratory experiments, ensuring accuracy and reliability.
• Utilize software tools such as TensorFlow, NumPy, and SPSS to preprocess, analyze, and visualize research data.
• Develop and implement algorithms and deep learning models to analyze complex biological datasets.
• Perform gel electrophoresis and other laboratory techniques to support experimental research objectives.
• Collaborate with research team members to design experiments, interpret results, and prepare reports and publications.

Skills

Data collection

Lab techniques

TensorFlow

NumPy

SPSS

Deep learning

Data analysis

Education

Masters degree in health data analytics or computational biology

Tools

TensorFlow

NumPy

SPSS

Job description

Elevate Clinical Research in Houston, TX seeks a Research Assistant to support healthcare and social assistance research by collecting, processing, and analyzing complex datasets for data-driven studies and experimental protocols.

The role involves collaboration with interdisciplinary teams to design methodologies, including computational and laboratory techniques, and to contribute to development and validation of machine learning models for biomedical data.