Johns Hopkins University
Research Software Engineer – Clinical NLP Specialty (Data Science and AI Institu
Johns Hopkins University, Baltimore, Maryland, United States, 21276
Overview
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, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves collaboratively with human intelligence, combining the strengths of each for the betterment of society and the world in which we live. DSAI will bring together the mathematical, computational, and ethical foundations of AI with the domains of Health & Medicine, Scientific Discovery, Engineered Systems, Security & Safety, and People, Policy & Governance. Research Software Engineer - Clinical NLP Specialty
with a strong academic background and relevant industry or academic experience focused on designing and building state-of-the-art clinical NLP systems. This position supports research initiatives in the development 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. The successful candidate will design, implement, evaluate, deploy and maintain robust and scalable NLP pipelines and models to extract meaningful information from unstructured clinical text in secure environments, enabling high-impact solutions across biomedical domains. Experience with large language models - such as fine-tuning, prompt engineering, model evaluation, and adapting foundation models for domain-specific clinical tasks - is desirable, particularly in contexts that demand privacy, robustness, and interpretability. The clinical NLP RSE will work closely with clinicians, informatics researchers, data scientists and other RSEs to ensure NLP systems meet application goals with methodological rigor and scientific reproducibility. DSAI engineers are at the forefront of modern data-intensive science, where professionally developed software is rapidly becoming a key ingredient for success. The DSAI initiative includes the build-out of a substantive and professional-scale software engineering capability, and a dramatic increase in infrastructure, both in hardware and in personnel. JHU has long been a world leader in medicine and public health as well as a wide range of science and engineering fields. This combined with our ethos of building capabilities to have demonstrable global impact (e.g., JHU Coronavirus Resource Center, the award-winning global resource for real-time data and analysis for COVID-19) and other large scientific data sets, will be key leverage points for DSAI's success. Specific Duties & Responsibilities
The successful candidates will participate in ground-breaking research projects that require advanced software solutions and expertise in software engineering not commonly found in scientific collaborations. The projects will involve the development of state-of-the-art clinical NLP solutions using the latest deep learning libraries and trained on state-of-the-art hardware in secure healthcare computing environments. Projects will analyze massive data sets either in the cloud or on premises. Projects will require development of novel NLP software pipelines for processing unstructured clinical notes. Some projects may involve deep engagement, potentially leading to co-authorship on scientific publications, while others may involve more casual consulting engagements. They may require software solutions developed from scratch or refactoring existing solutions to meet industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.). It is a high-level goal of DSAI to translate project efforts into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects. Special knowledge, skills, and abilities Strong NLP, LLM, machine learning and deep learning skills. Practical experience building NLP models and pipelines in a secure, HIPAA-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 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. Minimum Qualifications
Masters in a quantitative discipline such as computer science, engineering, physics or bioinformatics, with strong scientific computing and/or mathematics background. Three years of experience working in software development on large clinical NLP projects in industry or academia. Additional education may substitute for required experience, and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula. Preferred Qualifications
PhD in a quantitative discipline. Five (5) years’ experience as above in clinical NLP. Experience in CUDA GPU programming. Experience authoring open-source Python packages in PyPI. Experience in open-source project governance. Experience in open-source community adoption initiatives. Classified Title: Scientific Software Engineer Job Posting Title (Working Title): Research Software Engineer – Clinical NLP Specialty (Data Science and AI Institute) Role/Level/Range: APPTSTAF/01/ST Starting Salary Range: Commensurate w/exp. Employee group: Full Time Schedule: 37.5 hrs/wk, M-F FLSA Status: Exempt Location: Hybrid/Homewood Campus Department name: DSAI Institute Personnel area: Whiting School of Engineering The listed salary range represents the minimum and maximum Johns Hopkins University offers for this position, based on a good faith estimate at the time of posting. Actual compensation will vary depending on factors such as location, skills, experience, market conditions, education, and internal equity. Not all candidates will qualify for the highest salary in the range. Johns Hopkins provides a comprehensive benefits package supporting health, career, and retirement. Learn more: https://hr.jhu.edu/benefits-worklife/. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. EEO is the Law EEOC KnowYourRights6.12ScreenRdr.pdf
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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, in part through investments in the software engineering, data science, and machine learning space. DSAI is focused on revolutionizing discovery by advancing artificial intelligence that evolves collaboratively with human intelligence, combining the strengths of each for the betterment of society and the world in which we live. DSAI will bring together the mathematical, computational, and ethical foundations of AI with the domains of Health & Medicine, Scientific Discovery, Engineered Systems, Security & Safety, and People, Policy & Governance. Research Software Engineer - Clinical NLP Specialty
with a strong academic background and relevant industry or academic experience focused on designing and building state-of-the-art clinical NLP systems. This position supports research initiatives in the development 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. The successful candidate will design, implement, evaluate, deploy and maintain robust and scalable NLP pipelines and models to extract meaningful information from unstructured clinical text in secure environments, enabling high-impact solutions across biomedical domains. Experience with large language models - such as fine-tuning, prompt engineering, model evaluation, and adapting foundation models for domain-specific clinical tasks - is desirable, particularly in contexts that demand privacy, robustness, and interpretability. The clinical NLP RSE will work closely with clinicians, informatics researchers, data scientists and other RSEs to ensure NLP systems meet application goals with methodological rigor and scientific reproducibility. DSAI engineers are at the forefront of modern data-intensive science, where professionally developed software is rapidly becoming a key ingredient for success. The DSAI initiative includes the build-out of a substantive and professional-scale software engineering capability, and a dramatic increase in infrastructure, both in hardware and in personnel. JHU has long been a world leader in medicine and public health as well as a wide range of science and engineering fields. This combined with our ethos of building capabilities to have demonstrable global impact (e.g., JHU Coronavirus Resource Center, the award-winning global resource for real-time data and analysis for COVID-19) and other large scientific data sets, will be key leverage points for DSAI's success. Specific Duties & Responsibilities
The successful candidates will participate in ground-breaking research projects that require advanced software solutions and expertise in software engineering not commonly found in scientific collaborations. The projects will involve the development of state-of-the-art clinical NLP solutions using the latest deep learning libraries and trained on state-of-the-art hardware in secure healthcare computing environments. Projects will analyze massive data sets either in the cloud or on premises. Projects will require development of novel NLP software pipelines for processing unstructured clinical notes. Some projects may involve deep engagement, potentially leading to co-authorship on scientific publications, while others may involve more casual consulting engagements. They may require software solutions developed from scratch or refactoring existing solutions to meet industry standards (quality, efficiency, reusability, robustness, portability, documentation, etc.). It is a high-level goal of DSAI to translate project efforts into frameworks and template patterns for sustainable scientific infrastructure benefiting future projects. Special knowledge, skills, and abilities Strong NLP, LLM, machine learning and deep learning skills. Practical experience building NLP models and pipelines in a secure, HIPAA-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 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. Minimum Qualifications
Masters in a quantitative discipline such as computer science, engineering, physics or bioinformatics, with strong scientific computing and/or mathematics background. Three years of experience working in software development on large clinical NLP projects in industry or academia. Additional education may substitute for required experience, and additional related experience may substitute for required education beyond a high school diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula. Preferred Qualifications
PhD in a quantitative discipline. Five (5) years’ experience as above in clinical NLP. Experience in CUDA GPU programming. Experience authoring open-source Python packages in PyPI. Experience in open-source project governance. Experience in open-source community adoption initiatives. Classified Title: Scientific Software Engineer Job Posting Title (Working Title): Research Software Engineer – Clinical NLP Specialty (Data Science and AI Institute) Role/Level/Range: APPTSTAF/01/ST Starting Salary Range: Commensurate w/exp. Employee group: Full Time Schedule: 37.5 hrs/wk, M-F FLSA Status: Exempt Location: Hybrid/Homewood Campus Department name: DSAI Institute Personnel area: Whiting School of Engineering The listed salary range represents the minimum and maximum Johns Hopkins University offers for this position, based on a good faith estimate at the time of posting. Actual compensation will vary depending on factors such as location, skills, experience, market conditions, education, and internal equity. Not all candidates will qualify for the highest salary in the range. Johns Hopkins provides a comprehensive benefits package supporting health, career, and retirement. Learn more: https://hr.jhu.edu/benefits-worklife/. Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran. EEO is the Law EEOC KnowYourRights6.12ScreenRdr.pdf
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