Tenure Track Faculty in Artificial Intelligence/Human Computer Interaction/ Implementation Science (software focus)/Bioinformatics/Computational Biology/Computer Science/Biomedical Informatics/Biomedical Imaging Job Opening in Philadelphia, Pennsylvania

Qualifications:

Dental background and PhD in Artificial Intelligence, Human Computer Interaction, Implementation Science, Software Engineering, Bioinformatics, Computational Biology, Computer Science, Biomedical Informatics, Health Informatics, Data Science, or a related discipline with at least one year of postdoctoral research experience related to the health-related/dental field, a demonstrated record of significant research, the potential to make substantial contributions as an independent investigator, and a commitment to teaching professional, undergraduate, and graduate students.

Applicants must have successfully completed projects in machine learning (ML), deep learning (DL), or artificial intelligence (AI). He or she must have expertise in the life sciences, or public health, or computer sciences with strong background in computational biology, genomic analysis and general life sciences, and health research.

Preference will be for applicants with established research portfolio including NIH extramural funding and strong publishing record.

Candidates should have strong working knowledge of computational methods, software development frameworks, data analysis, and visualization tools relevant to their research expertise. Examples include Python, R, SQL, machine learning frameworks (PyTorch,

TensorFlow, Scikit-learn), data visualization tools, web-based application frameworks, and human-centered design and usability evaluation platforms. Experience with clinical data systems, EHR/EDR integration, and AI-enabled healthcare applications is highly desirable.

Programming with C++ or Java or Python is required. Experience developing, testing, and maintaining software applications is preferred.

Experience with developing, validating, and evaluating AI-driven software applications, clinical decision support systems, user interfaces, or digital health tools is highly preferred. Candidates with HCI expertise should demonstrate experience in user-centered design, usability testing, workflow analysis, user experience (UX) research, and human-AI interaction. Candidates with implementation science expertise should demonstrate experience in implementation frameworks, stakeholder engagement, workflow integration, adoption, feasibility, acceptability, and sustainability evaluation of healthcare technologies.

Experience with clustering algorithm is required such as K-means clustering, density-based clustering, distribution-based clustering, and Fuzzy clustering.

Experience with metric and non-metric multidimensional scaling, self-organized maps, artificial neural networks, fuzzy logic, neuro-fuzzy networks, and other pattern recognition and clustering methods is highly preferred.

Experience with database design, natural language processing, clinical data extraction, information retrieval, healthcare data standards, and interoperability frameworks such as HL7 FHIR is preferred but not necessary.

Experience with healthcare ontologies, terminology standards, knowledge representation, and data integration, including SNOMED CT, ICD, or related clinical terminologies, is preferred but not necessary.

Experience with human-centered evaluation of AI systems, including usability, explainability, transparency, clinician trust, and human-AI collaboration, is preferred but not necessary.

Experience with implementation science frameworks and methods, such as CFIR, RE-AIM, or hybrid effectiveness-implementation study designs, to evaluate adoption, integration, effectiveness, and sustainability of digital health technologies is preferred but not necessary.

Experience with software prototyping, application programming interfaces (APIs), cloud computing, software deployment, and integration of AI models into clinical systems is preferred but not necessary.

Experience with database design, natural language processing, and regular expressions to query gene and proteome sequences is preferred but not necessary.

AI expertise in multi-omics data integration, biological foundation models, and graph neural networks for biological discovery

Preferences

Preference will be given to applicants in collaborations with other researchers in the US and/ or other countries, especially on oral health and systemic health projects. Successful candidates will become part of a network of multidisciplinary and transdisciplinary research teams with relevant schools and colleges of Temple University. Research laboratory space and start-up package will be available.

Successful candidates will have primary responsibility for building a strong research program in oral health artificial intelligence/ bioinformatics. Responsibilities will also include didactic teaching and service. Salary and rank will be commensurate with experience and research production. Successful candidates will also be considered for senior administrative leadership positions at the school.

Temple University is an equal opportunity affirmative action employer. Women and minorities are encouraged to apply. For confidential consideration, interested individuals should email a cover letter, curriculum vitae and three references to Dr. Marisol Tellez Merchan