The Department of Internal Medicine at the Howard University College of Medicine is looking to advance healthcare delivery, improve patient outcomes, and address complex challenges in precision and population health through interdisciplinary projects focusing on Artificial Intelligence (AI), Machine Learning (ML), Computational Medicine, and Data Analytics.
Requirements
- Demonstrated proficiency in Python and related libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
- Familiarity with data analysis and visualization using tools such as Matplotlib, Seaborn, or Plotly.
- Foundational understanding of AI, machine learning, and data science concepts.
- Experience working with biomedical, clinical, or public health datasets.
- Familiarity with cloud computing platforms (e.g., AWS, Google Cloud, or Microsoft Azure).
- Experience with version control systems (e.g., Git/GitHub).
- Prior research or academic publication experience.
Responsibilities
- Assist with data collection, curation, preprocessing, and integration from diverse biomedical and clinical sources.
- Conduct exploratory data analysis, data visualization, and feature engineering.
- Develop, train, and evaluate machine learning and deep learning models.
- Review scientific literature and summarize findings to support ongoing research projects.
- Contribute to technical documentation, manuscripts, and progress reports.
- Collaborate effectively with interdisciplinary teams across research and clinical domains.
- Maintain accurate records of research workflows, results, and code repositories.
Other
- Current enrollment in a Bachelor’s, Master’s, or Ph.D. degree program in Computer Science, Data Science, Biomedical Engineering, or a related field.
- Must be at least a third-year undergraduate student (Junior or Senior status) or higher.
- Strong analytical thinking, problem-solving, and written communication skills.
- Ability to work independently and collaboratively in a research environment.
- Travel requirements not specified
