Assistant Professor in Biostatistics and Informatics

University of Colorado System; South Dakota; Hybrid; USD 120,000 - 180,000; Full time

Job summary

University of Colorado Anschutz in Colorado is seeking an innovative Assistant Professor in Biostatistics and Informatics to advance methodological research at the intersection of statistics, AI, and biomedical data science.

The role emphasizes collaboration, teaching, grant development, and student mentorship within a thriving, interdisciplinary environment that spans CU Anschutz and ColoradoSPH.

Responsibilities

• Develop innovative statistical methods integrating AI and data science for biomedical problems.
• Lead interdisciplinary collaborations across CU Anschutz and ColoradoSPH.
• Drive extramural grant applications (NIH) and manage research funding.
• Teach graduate courses in biostatistics, data science, and AI-enabled analytics.
• Mentor MPH, MS and PhD students in biostatistics and related fields.
• Publish in high-impact journals and present at conferences.
• Contribute to departmental governance and collaborative initiatives.

Skills

Machine learning

Deep learning

Causal inference

High-dimensional data

Multi-omics

Functional data analysis

Statistical genetics

Spatial statistics

Clinical trial design

Bayesian methods

Predictive modeling

AI in biostatistics

Job description

University of Colorado Anschutz

Department: Biostatistics and Informatics

Job Title: Assistant Professor

Position # 00854452: – Requisition #41665:

Job Summary:

The Department of Biostatistics and Informatics (BIOS) at the
Colorado School of Public Health (ColoradoSPH) invites applications for a full-time, tenure-eligible faculty appointment at the rank of
Assistant Professor. This is an exceptional opportunity to join one of the most dynamic and forward-thinking biostatistics departments in the nation. We are a department defined by methodological innovation, deep-rooted team science, and real-world biomedical impact at the intersection of statistics, data science, and artificial intelligence.

We are seeking a creative and collaborative biostatistician whose research interests complement and extend the department's strengths. Ideal candidates will bring expertise in one or more areas where modern statistical methodology intersects with advances in AI, data science, and biomedical research. Areas of interest include, but are not limited to, machine learning and deep learning for biomedical applications, AI-integrated statistical methods, causal inference, high-dimensional and multi-omics data analysis, methods for functional and digital health data, statistical genetics and genomics, spatial and imaging statistics, clinical trial design, Bayesian methods, and predictive modeling. We particularly welcome candidates whose methodological research demonstrates impactful applications in biomedical areas that align with the research strengths and collaborative opportunities of the
CU Anschutz. Examples include cancer research (e.g., molecular profiling, genomics, imaging, treatment selection, and therapeutic response), neuroscience (e.g., neuroimaging, neurophysiological signals, cognitive and neurodegenerative disorders, and models of disease progression), cardiovascular health (e.g., imaging, risk prediction, and clinical decision support), musculoskeletal health and orthopedics (e.g., imaging, movement and wearable sensor data, medical devices, surgical planning, and rehabilitation outcomes), transplantation (e.g., donor-recipient matching, rejection risk prediction, and long-term graft and patient outcomes), and other areas of translational, clinical, and population health research.
Successful candidates will be expected to develop innovative statistical methods while addressing important challenges in precision medicine, clinical research, population health, and related biomedical domains.

The successful candidate will join a department that is not siloed by subfield but organized around interdisciplinary problem-solving.
Faculty serve as co-investigators and collaborative partners across
CU Anschutz—one of the largest and most comprehensive academic health science centers in the country—with direct connections to the School of Medicine, College of Nursing, clinical departments, and leading research institutes. If you want your statistical methods to have a direct, tangible impact on human health, this department is where that happens.

Key Responsibilities

• Methodological Research: Develop innovative statistical and computational methods, with a focus on advancing the integration of modern biostatistical approaches with machine learning, AI, and data science tools applicable to biomedical and public health problems.
• Collaborative Research: Engage in substantive interdisciplinary collaborations across CU Anschutz, ColoradoSPH, and affiliated research institutes; serve as a co-investigator and statistical lead on funded studies in health sciences.
• Grant Development & Funding: Lead and contribute to the preparation and submission of extramural grant applications (NIH R01, R21, U01, and equivalent), securing independent and collaborative research funding to support an active research program.
• Teaching & Curriculum Development: Teach graduate-level courses in biostatistics, data science, and related methods for
  MPH, MS and PhD students; contribute to and innovate within the department's cutting-edge curriculum, including AI-integrated analytics and multi-omics training programs.
• Student Mentorship: Actively mentor MPH, MS and PhD students in biostatistics, guiding thesis and dissertation research, and contributing to the training of the next generation of quantitative public health scientists.
• Scholarly Contribution & Dissemination: Publish research in high-impact peer-reviewed journals; present at national and international scientific conferences; build a visible and influential scholarly presence in the field.
• Service & Departmental Citizenship: Contribute to departmental, school, and university service including committee participation, curriculum governance, and engagement in department collaborative science initiatives.

Supervision Received

The faculty member will be supervised by and report to the Chair of the Department of Biostatistics and
Informatics. The Chair and senior faculty are available for mentorship and guidance in research, teaching, and career development.

Supervision Exercised

This position may include supervisory responsibilities for graduate research assistants (MS and PhD students), postdoctoral fellows, and early-career research instructors or professional research assistants.

Work Location

Hybrid – this role is eligible for a hybrid schedule of 3 days per week on campus and as needed for in-person meetings.

Why Join Us

The Colorado School of Public Health is a collaborative endeavor involving the University of Colorado Anschutz Medical Campus (CU Anschutz), Colorado State University (CSU), and the University of Northern Colorado (UNC). The Colorado School of Public Health is the first and only accredited school of public health in the Rocky Mountain Region, attracting top-tier faculty and students from across the country and providing vital contributions towards ensuring our region's health and well-being. Collaboratively formed in 2008 by CU Anschutz, CSU, and UNC, the Colorado School of Public
Health provides education programs, including a Master's concentration in global health, innovative research that places the
School in the top 20 in NIH funding among Schools of Public Health, and community service that addresses public health issues including chronic disease, healthcare access, climate, and environmental threats, emerging infectious diseases, population mental health,
ONE HEALTH and injuries for the Rocky Mountain region, nationally and globally.

A Department at the Frontier of Biostatistics and AI

The Department of Biostatistics and Informatics is a methodologically and collaboration-driven department that integrates modern statistical theory with large-scale biomedical applications through deeply embedded team science and multi-institutional research networks. We develop statistical methods that directly shape the science of human health.

Our faculty span a broad and modern statistical toolkit, organized around several dominant methodological pillars that are actively pushing the frontier of what biostatistics can accomplish in the age of AI and big data:

• Causal Inference & Semiparametric Methods: Doubly robust estimation, measurement error correction, treatment effect heterogeneity, and real-world observational and clinical data challenges.
• High-Dimensional and Machine Learning Methods for Multi-omics
  Data Integration: Statistical learning, deep learning, clustering, networks, and mediation analysis applied the novel integration of genomics, transcriptomics, methylation, proteomics and metabolomics data.
• Statistical Genetics and Genomics: Methods for GWAS and polygenic risk scores with a strong focus on population differences and precision medicine.
• Latent Variable & Longitudinal Modeling: Latent class/profile models, joint models, and longitudinal data analysis for behavioral, clinical, and reproductive health data.
• Functional Data Analysis & Digital Health: Wearable sensor data, functional regression, and high-frequency longitudinal modeling applied to large-scale population datasets—an emerging departmental strength.
• Sampling Design & Clinical Trials: Adaptive Bayesian trial design, pharmacokinetics, and efficient sampling strategies, including FDA-interactive regulatory science.
• Spatial & Imaging Statistics: Spatial point processes, medical imaging analysis, and tumor microenvironment modeling at the interface of statistics and computational biology.

A Campus Built for Big Science

The University of Colorado Anschutz is the only comprehensive academic health sciences center in Colorado, the largest academic health center in the Rocky Mountain region, and one of the most dynamic medical campuses in the world. Home to more than 25,000 employees and 5,000+ degree-seeking students, CU Anschutz is a hub of discovery across medicine, pharmacy, nursing, dental medicine, and public health—with two nationally recognized hospitals handling
1.7 million patient visits annually.

Our department is deeply embedded in this ecosystem, collaborating across the School of Medicine, College of Nursing, epidemiology and clinical departments, and affiliated research institutes. A particularly close and natural partnership exists with the
Department of Biomedical Informatics (DBMI), a nationally recognized leader in AI for healthcare, clinical informatics, population genetics, and systems biology. With more than 40 primary faculty, $46M in research funding, and 30 innovative laboratories,
DBMI represents one of the fastest-growing academic units at CU
Anschutz and a department whose computational science is deeply complementary to the statistical rigor and methodological innovation of BIOS. Together, these two departments anchor the quantitative and data science enterprise at CU Anschutz