Heading

Saint Paul, MN

Internship

Onsite

$17.85/hr - $35.75/hr

Intern

Abbott is a global healthcare leader developing technologies across diagnostics, medical devices, nutritionals, and medicines. The PhD Co-op will support the Electrophysiology Clinical Affairs organization by developing predictive and multimodal machine learning models for clinical research, analyzing clinical data, and collaborating with clinical scientists and cross-functional stakeholders.

Apply Now

Responsibilities

Design, develop, train, evaluate and fine-tune predictive models for clinical trial enrollment forecasting, clinical outcomes and other clinical applications
Evaluate model performance using clinically relevant endpoints and validation methodologies
Build data pipelines for harmonizing and curating diverse clinical and procedural datasets
Perform data quality assessments, feature engineering, and model-ready dataset creation
Integrate and analyze large multimodal structured or unstructured datasets including medical imaging, clinical records, procedural data, adverse event data, and clinical trial datasets
Develop data pipelines, algorithms, and visualization tools
Track metrics and document results to improve model accuracy
Apply statistical, predictive, and generative AI techniques
Collaborate with clinical scientists to identify clinically meaningful questions, endpoints, and model performance criteria
Prepare technical reports, presentations, and recommendations
Collaborate with cross-functional stakeholders
Support scientific abstracts and publications

Qualification

Required

Currently enrolled in a Master's or PhD program in Computer Science, Bioinformatics, Computational Biology, Health Informatics, Engineering, or related field
Advanced proficiency in Python required
Experience with software development, version control, and code documentation
Familiarity with core machine learning concepts, statistics, and frameworks
Experience developing machine learning or advanced analytical models
Experience using Git for version control and familiarity with shell-based or cloud development environments
Knowledge of statistical analysis, predictive modeling, and data mining
Experience managing and analyzing large datasets
Strong problem-solving abilities and a demonstrated eagerness to research and learn new AI technologies independently
Strong analytical and problem-solving skills
Ability to work independently and manage multiple priorities
Strong written, verbal, and presentation skills
Ability to communicate complex technical concepts effectively
Collaborative mindset and intellectual curiosity

Preferred

PhD candidates preferred
experience with R, SQL, MATLAB, Julia, or other analytical programming languages preferred
Experience with deep learning, NLP, generative AI, or large language models
Familiarity with libraries such as PyTorch, TensorFlow/Keras, Scikit-learn or XGBoost/LightGBM preferred
Experience with multimodal AI, foundation models, or fusion methods combining imaging and structured clinical data
Established and shareable GitHub repository
Experience working with cardiac CT, cardiac MRI, echocardiography, fluoroscopy, DICOM data, or other cardiovascular imaging datasets
Experience with longitudinal data analysis, survival analysis, risk prediction modeling, or time-to-event methodologies
Publication record or demonstrated research excellence

Benefits

Career development with an international company where you can grow the career you dream of.
Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year.
An excellent retirement savings plan with a high employer contribution.
Tuition reimbursement.
The Freedom 2 Save student debt program.
FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree.

Abbott is a healthcare company that produces diagnostic kits, medical devices, nutritional products, and branded generic medicines.

Glassdoor