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Post-Doctoral Fellow
Post-Doctoral Fellow - 36139 Faculty Description
University of Colorado Anschutz Medical Campus
Department: Biomedical Informatics
Job Title: Post-Doctoral Fellow
Position #00831821: - Requisition #:36139
Job Summary:
The McConnell Lab and the Krishnan Lab are seeking a Postdoctoral Fellow in a joint-mentored collaboration within the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus. Additional mentoring support will be provided by Dr. Ashis Biswas, Dr. Nicholas Dwork, and a multidisciplinary team of clinical neuroscientists and data scientists. This position is funded by an NIH R01 and will focus on developing digital biomarkers for early detection of neurodegeneration using single-channel sleep EEG. Candidates with a strong background in computational biology, bioinformatics, signal processing, machine learning, and related fields are encouraged to apply.
The fellow will play a key role in advancing the objectives of the R01, contributing to the development of computational approaches for analyzing oscillatory features in sleep EEG that predict brain aging, cognitive decline, and Alzheimer's disease-related biomarkers. In addition to helping achieve the specific aims of the grant, the fellow will be encouraged to explore independent research questions related to digital biomarkers, brain aging, and computational neuroscience, with strong mentorship and career development support from the Principal Investigator (PI) and Co-Investigators (Co-Is).
Training Environment
The fellow will benefit from a multidisciplinary, collaborative research environment with mentorship from experts across neuroscience, computational biosciences, bioinformatics, and artificial intelligence.
- Dr. Brice McConnell, MD, PhD (PI) leads research on sleep and neurodegeneration, directing the Sleep Research Program at the University of Colorado Alzheimer's and Cognition Center. His lab focuses on:
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- Developing digital biomarkers from wearable EEG devices for early detection of brain aging and neurodegeneration.
- Investigating the neuroprotective role of sleep in aging and neurodegenerative disease.
- Linking brain network changes to molecular phenotypes associated with early Alzheimer's disease pathology.
- Dr. Arjun Krishnan, PhD (Co-I) is an Associate Professor in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus. His lab's goals include:
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- Defining mechanistic subtypes of disease using multi-omics and computational models.
- Revealing age- and sex-specific physiological changes in neurodegeneration.
- Translating insights from human and model systems to uncover novel biomarkers.
- Dr. Ashis Kumer Biswas, PhD (Co-I) is an Assistant Professor in the Department of Computer Science and Engineering at the University of Colorado Denver and the Director of the Machine Learning Lab. His expertise includes:
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- Developing novel deep learning and machine learning algorithms for biomedical and health applications.
- Applying responsible AI principles to ensure privacy-aware and interpretable AI models.
- Leveraging bioinformatics and multi-omics data integration to explore disease associations and biomarker discovery.
- Dr. Nicholas Dwork, PhD (Co-I) is an Assistant Professor in the Department of Biomedical Informatics at the University of Colorado Anschutz Medical Campus. His lab specializes in:
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- Developing advanced mathematical models to accelerate and enhance magnetic resonance imaging (MRI) for clinical applications.
- Applying optimization techniques to improve quantitative optical coherence tomography (OCT) and radiation treatment planning.
- Physics-informed AI methods that integrate prior knowledge of biological and physical systems to improve data-driven modeling of physiological signals.
Drs. McConnell, Krishnan, Biswas, and Dwork will provide collaborative mentorship and training, ensuring a strong foundation in computational neuroscience, digital biomarkers, and advanced machine learning methods. The research environment encourages both structured project work and the development of independent research directions.
Project Context & Research Focus
Alzheimer's disease is a leading cause of death in the U.S., and scalable digital tools for prevention and early detection are critically needed. Our team is developing machine learning-driven digital biomarkers from wearable sleep electroencephalography (EEG) data to assess neurodegenerative changes before clinical symptoms emerge.
The fellow will help refine and validate computational models using large-scale, multi-cohort EEG data, applying advanced signal processing, deep learning, and bioinformatics approaches to:
- Brain aging phenotypes - Identifying youthful vs. accelerated brain aging through EEG-based features.
- Cognitive decline trajectories - Mapping sleep oscillatory circuit integrity to cognitive performance.
- Neuroimaging & biomarker correlates - Linking EEG-derived metrics to AD-related molecular and structural changes.
This work aims to establish sleep EEG as a practical, scalable, and cost-effective digital biomarker for early Alzheimer's disease detection and brain health monitoring.
Supervision Received:
The Postdoctoral Fellow will administratively report to Dr. Arjun Krishnan, and will receive co-mentorship and additional supervision from Dr. Brice McConnell, Dr. Ashis Biswas, and Dr. Nicholas Dwork.
Professional Field:
- Machine Learning & Data Science
- Biomedical Sciences & Neuroscience
- Computational Biology & Bioinformatics
Key Responsibilities:
The fellow's work will align with the specific aims of the supporting R01 grant, with structured mentorship and opportunities for independent research.
70% Primary Research - R01 Objectives & Independent Investigations
- Develop and implement advanced computational pipelines for analyzing oscillatory event features in large-scale sleep EEG datasets.
- Design and optimize machine learning models to predict brain aging, cognitive decline, and neurodegenerative biomarkers from EEG data.
- Refine signal processing methods for detecting key sleep oscillatory events and improve their interpretability as neurophysiological markers.
- Work closely with the PI, Co-Is, and interdisciplinary collaborators (neuroscientists, sleep researchers, computational biologists, and clinicians) to integrate EEG features with cognitive, neuroimaging, and biomarker data.
- Maintain well-documented, reproducible code and contribute to open-source methodologies.
- Pursue independent research directions that complement the project's objectives and align with the fellow's career trajectory.
15% Communication & Scientific Dissemination
- Present research progress at lab meetings, departmental seminars, and project team discussions.
- Disseminate findings through first-author publications and conference presentations.
- Participate in grant writing, including fellowship applications for independent funding and contributions to collaborative grant proposals.
5% Mentorship & Training
- Develop computational workflows and best practices for signal processing and machine learning in EEG research.
- Mentor graduate students and research associates by providing guidance on EEG analysis and computational techniques.
5% Administrative & Research Compliance
- Ensure adherence to data management protocols for multi-cohort EEG datasets.
- Complete required institutional and NIH research trainings.
- Assist with general lab organization and collaborative research efforts.
5% Career Development & Professional Growth
- Engage in professional development activities, including workshops, networking events, and individualized career mentorship.
- Develop an Individualized Development Plan (IDP) with the PI and Co-I and update it annually.
- Stay active in the scientific community by attending relevant meetings and maintaining an updated CV.
Work Location:
We are a hybrid in-person/remote group, with flexibility as needed and in agreement with the PI.
Why Join Us:
This position offers a unique opportunity to contribute to an NIH-funded project with high translational impact, applying advanced computational techniques to develop scalable, real-world digital biomarkers for brain health monitoring. The fellow will:
- Gain expertise at the intersection of neuroscience, digital biomarkers, wearable health technology, and advanced computational modeling, including neural network-based approaches to machine learning.
- Work with a diverse team of experts in sleep research, aging, neurodegenerative disease, computational neuroscience, biomedical data science, and translational neurotechnology.
- Develop and refine computational pipelines for analyzing large-scale EEG datasets, integrating signal processing, statistical modeling, and machine learning-based feature extraction.
- Apply deep learning, time-series modeling, and bioinformatics approaches to characterize neurophysiological markers associated with brain aging and Alzheimer's disease.
- Receive personalized mentorship while having the freedom to explore independent research directions and establish an early-career research trajectory.
- Build a competitive academic or industry career path in computational neuroscience, bioinformatics, neurotechnology, and biomedical AI applications.
Why work for the University?
The University of Colorado offers a comprehensive benefits package. To see what benefits are available for Post-Doctoral Fellows, please visit:
Payroll & Benefits Orientation for Post-Doctoral Fellows | University of Colorado (cu.edu)
benefits guide cover-post-doc-2024 (cu.edu)
Diversity and Equity:
The University of Colorado Anschutz Medical Campus is committed to recruiting and supporting a diverse student body, faculty and administrative staff. The university strives to promote a culture of inclusiveness, respect, communication and understanding. We encourage applications from women, ethnic minorities, persons with disabilities, persons within the LGBTQ+ community and all veterans. In addition, the Anschutz Campus has also been recognized as an Age-Friendly University. The University of Colorado is committed to diversity and equality in education and employment.
Qualifications:
Minimum Qualifications:
Applicants must meet minimum qualifications at the time of hire.
- PhD in a quantitative field (e.g., computational neuroscience, bioinformatics, biomedical engineering, data science, or a related discipline).
- At least 3 years of experience using R, Python, and/or a comparable programming language, preferably in a high-performance computing environment with Linux command-line expertise and advanced use of version control (e.g., Git).
Preferred Qualifications:
- Experience developing and/or applying machine learning methods to a problem in some domain such as biology, social science, economics, etc.
- Proficiency in scientific communication with a track record of first-author publications in peer-reviewed journals and oral presentations at national or international conferences.
- Hands-on experience with the Python data science and machine learning stack, including (but not limited to) pandas, matplotlib, scikit-learn, and/or PyTorch.
- Evidence of effective collaboration in team-based research and a positive contribution to colleagues' projects.
- Prior experience working with EEG data or related physiological time-series data.
Knowledge, Skills and Abilities:
- Demonstrated willingness to give and receive constructive feedback, fostering a supportive and inclusive lab environment.
- Strong interest in brain aging, sleep neurophysiology, and neurodegeneration.
- Demonstrated ability to work both independently and collaboratively within an interdisciplinary research environment.
How to Apply:
For full consideration, please submit the following document(s):
- A letter of application (1-2 pages) which specifically addresses qualifications for the job requirements and describes research interests noting the alignment of these interests with the McConnell Lab's and Krishnan Lab's research programs
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: DBMI.HR <dbmi.hr@cuanschutz.edu>
Screening of Applications Begins:
Anticipated Pay Range:
The starting salary range (or hiring range) for this position has been established as HIRING RANGE:
$73,000
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
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.
Application Materials Required: Cover Letter, Resume/CV, List of References, Additional Attachments - Refer to Application Materials Instructions Below Job Category
: Faculty Primary Location
: Aurora Department: U0001 -- Anschutz Med Campus or Denver - 21925 - SOM-BIOMED Informatics Gen Ops Schedule
: Full-time Posting Date
: Feb 6, 2025 Unposting Date
: Ongoing Posting Contact Name: DBMI.HR Posting Contact Email: dbmi.hr@cuanschutz.edu Position Number: 00831821
To apply, visit https://cu.taleo.net/careersection/2/jobdetail.ftl?job=36139&lang=en
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