Assistant Professor

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, creating exceptional opportunities for joint research, co-mentorship, and collaborative training at the intersection of biostatistics, informatics, and artificial intelligence. The Center for Innovative Design and Analysis (CIDA) embeds our statisticians directly within research teams across campus, while the CU Biostatistics and Bioinformatics Ecosystem (CUBE) coordinates analytic resources across the entire CU Anschutz enterprise. Faculty have immediate access to some of the richest biomedical data environments anywhere-including EHR systems, biobanks, imaging archives, and genomic cohorts-and the computing infrastructure to match.

A Training Ecosystem Like No Other

Our department operates a comprehensive, multi-level training ecosystem spanning formal graduate education, professional certificates, and continuing education. The new faculty member will have the opportunity to teach and mentor within:

* Graduate Degree Programs: MPH (AI-focus track), MS in Biostatistics, and PhD in Biostatistics-with a PhD curriculum that emphasizes methodological innovation and translational impact.

* AI-Analytics Series: A forward-looking curriculum integrating AI tools and methods into biostatistics training, preparing students for the rapidly evolving landscape of health data science.

* Colorado Summer Institute in Biostatistics (CoSIBS): An NIH-funded summer program that introduces students to biostatistics through lectures, labs, mentored research, and hackathons.

* CIDA & CUBE Learning Ecosystem: Short courses, CU Data Week hackathons, Big Data Seminar Series, and applied data science workshops serving researchers at all career stages.

An Exceptional Place to Live and Work

The Denver metropolitan area consistently ranks among the top cities in the United States for quality of life, offering a dynamic urban environment, a thriving innovation and technology ecosystem, outstanding schools, and a vibrant arts, food, and cultural scene. Colorado's rare combination of intellectual energy and natural beauty means that world-class skiing, hiking, and climbing in the Rocky Mountains are just an hour from campus, making it one of the most exciting and sought-after places in the country to build both a flourishing academic career and an active, fulfilling life.

Why work for the University?

We have AMAZING benefits and offer exceptional amounts of holiday, vacation and sick leave! The University of Colorado offers an excellent benefits package including:

• Medical: Multiple plan options
• Dental: Multiple plan options
• Additional Insurance: Disability, Life, Vision
• Retirement 401(a) Plan: Employer contributes 10% of your gross pay
• Paid Time Off: Accruals over the year (based on percentage of time)
• Vacation Days: 22/year (maximum accrual 352 hours)
• Sick Days: 15/year (unlimited maximum accrual)
• Holiday Days: 11/year
• Tuition Benefit: Employees have access to this benefit on all CU campuses
• ECO Pass: Reduced rate RTD Bus and light rail service

There are many additional perks & programs with the CU Advantage.

How to Apply:

For full consideration, please submit the following document(s):

1. A letter of interest describing relevant job experiences as they relate to listed job qualifications and interest in the position
2. Curriculum vitae / Resume
3. Five professional references including name, address, phone number (mobile number if appropriate), and email address

Applications are accepted electronically ONLY at www.cu.edu/cu-careers.

Questions should be directed to: David Conti, PhD, Chair, Department of Biostatistics and Informatics, david.conti@cuanschutz.edu

Screening of Applications Begins:

Applications will be accepted until finalists are identified, but preference will be given to complete applications received by January 15, 2027. Those who do not apply by this date may or may not be considered.

Anticipated Pay Range:

The starting salary range (or hiring range) for this position has been established as HIRING RANGE:

$120,000 to $150,000

The above salary range (or hiring range) represents the University's good faith and reasonable estimate of the range of possible compensation at the time of posting. This position is not eligible for overtime compensation unless it is non-exempt.

Your total compensation goes beyond the number on your paycheck. The University of Colorado provides generous leave, health plans and retirement contributions that add to your bottom line.

Total Compensation Calculator: http://www.cu.edu/node/153125

Equal Employment Opportunity Statement:

The University of Colorado (CU) is an Equal Opportunity Employer and complies with all applicable federal, state, and local laws governing nondiscrimination in employment. We are committed to creating a workplace where all individuals are treated with respect and dignity, and we encourage individuals from all backgrounds to apply, including protected veterans and individuals with disabilities.

ADA Statement:

The University will provide reasonable accommodations to applicants with disabilities throughout the employment application process. To request an accommodation pursuant to the Americans with Disabilities Act, please contact the Human Resources ADA Coordinator at hr.adacoordinator@ucdenver.edu.

Background Check Statement:

The University of Colorado Anschutz Medical Campus is dedicated to ensuring a safe and secure environment for our faculty, staff, students and visitors. To assist in achieving that goal, we conduct background investigations for all prospective employees.

Vaccination Statement:

CU Anschutz strongly encourages vaccination against the COVID-19 virus and other vaccine preventable diseases. If you work, visit, or volunteer in healthcare facilities or clinics operated by our affiliated hospital or clinical partners or by CU Anschutz, you will be required to comply with the vaccination and medical surveillance policies of the facilities or clinics where you work, visit, or volunteer, respectively. In addition, if you work in certain research areas or perform certain safety sensitive job duties, you must enroll in the occupational health medical surveillance program.

Minimum Qualifications:

Applicants must meet minimum qualifications at the time of hire.

* PhD degree in biostatistics, statistics, mathematics, computer science, applied mathematics, or a closely related discipline with equivalent training providing the required knowledge, skills, and abilities.

* Evidence of independent research through publications as first or corresponding author.

* Demonstrated potential for an independent, extramurally funded research program.

* Excellent oral and written communication skills.

* Demonstrated interest and excellence in graduate teaching and mentoring.

Preferred Qualifications:

* Postdoctoral research experience in biostatistics, statistics, or a related quantitative discipline.

* Demonstrated expertise in one or more methodological areas aligned with departmental strengths: causal inference, machine learning/AI, statistical genetics/genomics, multi-omics data integration, clinical trial design, Bayesian methods, longitudinal/functional data analysis, digital health, spatial statistics, or imaging analysis.

* Track record of extramural funding or documented progress toward independent funding (e.g., K99/R00, F32, career development awards).

* Demonstrated experience in collaborative biomedical research, with evidence of substantive co-investigator contributions to funded projects.

* Experience in teaching or mentoring graduate students or trainees in statistics, data science, or related quantitative fields.

* Demonstrated ability to lead the biostatistical design and analytic components of clinical or translational research studies.

* Experience with or strong interest in integrating AI tools and methods into biostatistical research and education.

Knowledge, Skills and Abilities:

* Deep knowledge of statistical theory and principles relevant to biomedical and public health research.

* Proficiency in statistical programming using R, Python, SAS, or equivalent; experience with high-performance computing and reproducible research workflows (e.g., GitHub, containers) is highly desirable.

* Strong knowledge of modern machine learning and/or AI methods with capacity for rigorous statistical integration.

* Excellent organizational, project management, and collaborative skills across multi-investigator research teams.

* Exceptional written and verbal communication skills, with ability to effectively communicate complex quantitative methods to different scientific audiences.

* Positive, collegial attitude and demonstrated ability to work effectively with biomedical investigators, students, and colleagues across the department, school, and CU Anschutz campus.

* Commitment to mentorship and the professional development of trainees.

* Strong problem-solving skills and intellectual creativity in the face of novel methodological challenges.