Future Talent Program Co-op - Patient Data Learning

Merck; Cambridge (MA); Presencial; USD 40.000 - 111.000; Jornada completa

Descripción de la vacante

Merck’s Future Talent Program in the Data, AI, and Genome Sciences department offers a six-month co-op in the Patient Data Learning group in Cambridge, MA. You will work on computational projects to develop skills and evaluate long-term fit with the company.

The role seeks highly motivated students with computational skills, eager to implement tools for feasibility questions and contribute to precision genetics research.

Formación

• Currently enrolled in a Master's program (or PhD encouraged) in a biomedical/clinical informatics related field.
• Strong software engineering fundamentals and experience with local LLMs and agent development practices.
• Proficiency in Python and SQL, with database-agnostic querying capability.
• Experience with querying structured EMR/EHR data or demonstrated interest in clinical applications.

Responsabilidades

• Design and build agent-assisted systems to explore phenotypes and clinical profiles in EHR-linked biobanks.
• Reuse and customize AI language models to translate clinical questions into machine queries.
• Create guardrails and evals to measure model and agent reliability.
• Assist applying these tools to feasibility questions in a collaborative setting.

Conocimientos

Biomedical Applications

Biomedical Informatics

Biomedical Sciences

Clinical Information Systems

Clinical Research

Data Analysis

Database Management

Data Engineering

Data Science

Data Security

Data Visualization

Econometrics

Epidemiology

Epidemiologic Methods

Medical Informatics

NLP

Python

R

Reliability Analysis

Tidyverse

Educación

Master's in Clinical Informatics / related field

Herramientas

Databricks

IBIS

Descripción del empleo

The Future Talent Program within the Data, AI, and Genome Sciences (DAGS) Department is offering co-op opportunities that last a period of six months. There is one position in the Patient Data Learning group. Candidates can apply for the opportunity to be involved in a computational project designed to enable students to further develop their skills and to evaluate if we are the right company for their long-term goals. We are seeking highly motivated and talented students with computational skills and experience.

Patient Data Learning in Precision Genetics (1 position, Cambridge MA)

• Design and build agent-assisted system or components to support feasibility assessment and early exploration of phenotypes and clinical profiles of patients in EHR-linked biobanks.
• Re-use and customize AI language models to turn scientific questions expressed in natural language into machine-generated queries to be evaluated in agentic loops.
• Create guardrails and evals to promote and measure the reliability of models and agents.
• Assist with the application of these tools and technologies to answer feasibility questions.

Required Education and Skills

• Currently enrolled in a minimum of a Master's degree program in Clinical Informatics, Epidemiology, Computational Medicine, Biomedical Informatics, Biostatistics, Computer Science with strong interest in biomedical applications, or a related field of study. Students enrolled in a PhD program are highly encouraged to apply.
• Computational/software engineering fundamentals sufficient to be able run and tune local LLMs, build local agentic systems, and comfortable with applying or outlining software and agent development practices (version control, packaging, tests & evals).
• Proficiency in Python, SQL, ideally database-agnostic querying such as ibis
• Applied knowledge sufficient to query structured EMR/EHR data, for example to create patient features, build cohorts, or report summary statistics, or a demonstrated interest in learning to do so and clinical applications.
• Available to work full-time for 6 months in 2027-2028 as part of a formal co-op program.
• Excellent academic achievement and analytical ability.
• Demonstrated superior communication and interpersonal skills and must be able to work well in a collaborative team environment.

Preferred Skills and Experience

• General interests/experience in ANY of the fields of clinical informatics, clinical machine learning, computational medicine, natural language processing and LLM research, epidemiology
• Good data systems fundamentals, and have at least notions of data engineering and database-agnostic design.
• Agent reward systems
• Knowledge in statistical methods for epidemiology or econometrics.
• Familiarity for the OMOP CDM and medical coding system (ICD, SNOMED, CPT, LOINC, etc.)
• Experience with Databricks.
• Knowledge of R and tidyverse packages.

Please note that this position may be closed before the posted end date or may remain open longer, at the discretion of the company.

Salary range

The salary range for this role is $39,908 - $111,111

Required Skills

Biomedical Applications, Biomedical Informatics, Biomedical Sciences, Clinical Information Systems, Clinical Research, Data Analysis, Database Management, Data Engineering, Data Science, Data Security, Data Visualization, Econometrics, Epidemiologic Methods, Epidemiology, Medical Informatics, Natural Language Processing (NLP), Python (Programming Language), Reliability Analysis, R Package, Software Proficiency, Statistical Methods, Tidyverse (R Package)

Preferred Skills

US and Puerto Rico Residents Only:

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