Focus areas for VCLIC include clinical decision support, artificial intelligence, machine learning ... genome-informed model. These advances have allowed VUMC to be known as a state-of-the-art ...
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Physics Informed Machine Learning information
What are the key skills and qualifications needed to thrive in the Physics Informed Machine Learning position, and why are they important?
To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.
What are the typical challenges faced by professionals working in Physics Informed Machine Learning roles?
Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.
What is a Physics Informed Machine Learning job?
A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.
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Faculty Member in: The Vanderbilt Clinical Informatics Center (VCLIC)
Nashville, TN • On-site
Full-time
Re-posted 9 days ago
Vanderbilt University rating
8.0
Based on 39 frontline employees who took The Breakroom Quiz
165th of 555 rated colleges and universities
Job description
Position Details: The Vanderbilt Clinical Informatics Center (VCLIC) and the Department of Biomedical Informatics (DBMI) at Vanderbilt University Medical Center (VUMC) are seeking a faculty member with expertise in clinical informatics. This position is focused on leading the development and implementation of advanced EHR-centric applied clinical informatics research. Focus areas for VCLIC include clinical decision support, artificial intelligence, machine learning, predictive analytics, and using the EHR to improve quality and safety. VCLIC and DBMI provide an unparalleled opportunity to do hands-on clinical informatics research in a real clinical setting, with outstanding access to data and the ability to test interventions in the real world.
Applicants for this position should submit a cover letter, CV, and the names and contact information of a minimum of three references. The cover letter should describe the applicant's relevant qualifications and experience, as well as brief statements of research and teaching interests. If you have questions about the application please reach out to elise.russo@vumc.org
VUMC DBMI is an internationally recognized leader in biomedical informatics, with strong relationships to academic departments in the university and the clinical operations of a large medical center. DBMI has an emphasis on interdisciplinary research, with a focus on health information technology development, clinical knowledge and workflow modeling, implementation sciences, machine learning and clinical decision support, biomedical data analytics (clinical, genomic, and proteomic), and natural language processing, privacy, and security.
Among more than 90 faculty are multiple members of the National Academy of Medicine, fellows of the American College of Medical Informatics, and fellows of AMIA. DBMI faculty hold additional appointments in various departments, including internal medicine, anesthesiology, biochemistry, biomedical engineering, computer science, hematology and oncology, human genetics, and pediatrics.
DBMI faculty often create and maintain readily accessible, large-scale operational clinical information systems, through which new scientific hypotheses are tested and new technologies are deployed. VUMC has benefited from over 15 years using an integrated, longitudinal electronic patient charting system. This system, now the foundation of our enterprise architecture on which Epic EHR sits, also distributes data to a research data warehouse linked to a biobank.
In addition to a robust set of conventional decision-support capabilities at the point of care, VUMC was the first center to include genetic information in EHR-driven clinical decision support through the computerized provider order-entry system and electronic prescribing application in order to guide providers to dose selected medications according to a genome-informed model. These advances have allowed VUMC to be known as a state-of-the-art laboratory for innovations that support population health, as recognized by groups such as NIH, PCORI, CMS, and AHRQ, through ongoing funding to members of our DBMI and School of Medicine faculty.
DBMI has established 5 Centers to provide support for software development and computational infrastructure management. Candidates for this position will work in the Vanderbilt Clinical Informatics Center, but will have the opportunity to collaborate across centers and departments at VUMC. The Vanderbilt Clinical Informatics Center (VCLIC), directed by Dr. Adam Wright, coordinates clinical informatics activities across Vanderbilt University Medical Center. VCLIC is working to "pave the road" for clinical informatics researchers and practitioners, ensuring that faculty, students, and staff throughout Vanderbilt find it easy to access data, test innovations, and evaluate results. VCLIC also offers lectures, training sessions, competitions, and funding opportunities for Vanderbilt informaticians. More information may be found at vumc.org/vclic.
Vanderbilt University Medical Center is an equal-opportunity, affirmative-action employer. Applications from women and members of under-represented minority groups are strongly encouraged. For more information, please visit the DBMI web site at www.vumc.org/dbmi.
Qualifications
The successful applicant will be able to immediately engage in ongoing grant-funded work to develop state-of-the-art care coordination and population management tools. As a part of a highly productive, highly supportive interdisciplinary team of researchers, informatics leaders, and clinical experts, this person will utilize biomedical informatics and computational methods to develop and integrate tools into real-world enterprise-wide healthcare settings. Candidates for this position should hold either a doctorate in informatics, computer science, or a related discipline, or a medical degree with demonstrated experience/training in informatics at a level suitable for subspecialty certification in clinical informatics.
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Nashville, TN, US
Year founded
1873