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Inside Higher Ed · 13 hours ago

Research Software Engineer - Clinical NLP Specialty (Data Science and AI Institute)

Baltimore, MD

Full-time

Hybrid

Mid, Senior Level

3+ years exp

The Johns Hopkins Data Science and AI Institute (DSAI) is a new pan-institutional initiative at Johns Hopkins to advance artificial intelligence and its applications. They are seeking a Research Software Engineer with expertise in designing and building clinical NLP systems to support research initiatives and develop novel NLP software pipelines for processing unstructured clinical text.

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Responsibilities

The successful candidates will participate in ground-breaking research projects that need advanced software solutions requiring expertise in software engineering not commonly found in scientific collaborations

The projects will require development of state-of-the art clinical NLP solutions using the latest deep learning libraries trained on state-of-the-art hardware in secure healthcare computing environments

Projects will involve analysis of massive data sets either in the cloud or on premises

Projects will require development of novel NLP software pipelines for processing of unstructured clinical notes

Some projects may require deep engagement, possibly leading to co-authorship on scientific publications, while others may involve a more casual consulting engagement

They may require software solutions developed from scratch or refactoring existing solutions to make them conform to industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.)

It is a high-level goal of DSAI to translate the efforts for the individual projects into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects

Qualification

NLPLarge Language ModelsMachine LearningDeep LearningPythonHIPAA CompliancePrompt EngineeringDockerLinuxGitCloud DevelopmentC++DatabricksTeachingCommunicationLeadershipContinuous Learning

Required

Strong academic background and relevant experience in industry or academia focused on designing and building state-of-the art clinical NLP systems

Experience with large language models - such as fine-tuning, prompt engineering, model evaluation, and adapting foundation models for domain-specific clinical tasks

Experience in developing and novel application of NLP and large language models to extract insights from unstructured clinical text using techniques such as named entity recognition (NER), negation detection, structured data extraction, diagnosis prediction, risk stratification, temporal reasoning and phenotyping

Strong NLP, LLM, machine learning and deep learning skills

Practical experience building NLP models and pipelines in a secure, HIPPA compliant healthcare environment

Expert-level knowledge of multiple modern NLP and LLM libraries and models

Hands-on experience adapting and fine-tuning large language models for domain-specific clinical applications, with attention to data efficiency, interpretability, and reproducibility

Demonstrated expertise in prompt engineering, evaluation, and benchmarking of large language models, including applying responsible AI principles in clinical or sensitive-data contexts

Expert-level knowledge of the Python programming language

Familiarity with or willingness to learn C++ or other languages as may be needed

Familiarity with software containerization technologies such as Docker and Singularity

Familiarity with the Databricks platform

Fluency in the Linux operating system and related tools

Familiarity with modern software engineering best practices, such as Git source control, peer code review, test-driven development, build automation and continuous integration / continuous delivery

Familiarity with cloud development and deployment

Demonstrated leadership and self-direction

Willingness to teach others both informally and in short course format

Willingness to continually learn new tools and techniques as needed

Excellent verbal and written communication

Masters in a quantitative discipline such as computer science, engineering, physics or bioinformatics, with strong scientific computing and/or mathematics background

Three year's experience working in software development in large clinical NLP projects in industry or academia