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Job Location (Full Address):

601 Elmwood Ave, Rochester, New York, United States of America, 14642

Opening:

Worker Subtype:

Regular

Time Type:

Full time

Scheduled Weekly Hours:

40

Department:

400626 Psychiatry M&D Research

Work Shift:

UR - Day (United States of America)

Range:

UR URG 110

Compensation Range:

$60,431.00 - $84,603.00

_The referenced pay range represents the minimum and maximum compensation for this job. Individual annual salaries/hourly rates will be set within the job's compensation range, and will be determined by considering factors including, but not limited to, market data, education, experience, qualifications, expertise of the individual, and internal equity considerations._

Responsibilities:

Job Description Summary

GENERAL PURPOSE

Dr. Paulo Lizano operates a Translational Neuroscience laboratory at the University of Rochester Medical Center in the department of psychiatry. The lab focuses on clinical, translational, and basic neuroscience projects that related to how vision and barrier disruption contribute to the development and neuroprogression of psychosis. This specific role will support projects funded by the National Institute of Mental Health to study the role of the retina and brain, and how they intersect with various cellular and molecular pathways related to barrier systems dysfunction in psychosis spectrum disorders and neuropsychiatric disorders more broadly. This full-time Data Scientist position will be part of the Lizano Translational Neuroscience research lab to play a crucial role in uncovering patterns in complex biological and behavioral data to better understand mental health and brain function for a variety of projects being conducted in the Lizano lab. The role will involve data collection & cleaning, data integration, preprocessing and cleaning, exploratory data analysis, statistical and computational modeling (including bioinformatic and AI tools), hypothesis testing and discovery science, visualization and data interpretation, communication of the findings, interdisciplinary collaboration among the different members of the team, and reproducibility and ethics for working with patient related data. The Lizano lab utilizes local data sets collected from past and current studies, as well as using openly available datasets, which are conducted in conjunction with international partners.

ESSENTIAL FUNCTIONS

+ Data Integration: Merging data from multiple sources such as neuroimaging (e.g., fMRI, EEG), clinical assessments, electronic health records, behavioral measures, proteomic measures, and potentially genetic data,.

+ Preprocessing & Cleaning: Handling noise and artifacts in biological signals, ensuring data quality, and preparing data for analysis—especially important for brain imaging and genetic data.

+ Statistical & Computational Modeling: Applying artificial intelligence, machine learning, deep learning, and statistical techniques to identify biomarkers, predict disease onset or progression (e.g., schizophrenia, depression), or classify subtypes of psychiatric disorders.

+ Hypothesis Testing & Discovery Science: Supporting hypothesis-driven research (e.g., testing the effect of a treatment on brain activity) and conducting exploratory analyses to uncover new findings.

+ Visualization & Interpretation: Creating intuitive visualizations of brain activity patterns, symptom trajectories, or genetic associations to help neuroscientists and clinicians understand complex results.

+ Interdisciplinary Collaboration: Working closely with neuroscientists, psychiatrists, psychologists, and bioinformaticians to ensure analytical approaches align with research goals and clinical relevance.

+ Reproducibility & Ethics: Ensuring analyses are reproducible, transparent, and comply with ethical standards, especially when dealing with sensitive patient data.

Other duties as assigned

MINIMUM EDUCATION & EXPERIENCE

+ Bachelor's degree in Data Science, Math, Information Science or related field REQUIRED.

+ 1 year of relevant experience REQUIRED.

+ Or an equivalent combination of education and experience REQUIRED.

+ Master's Degree preferred

KNOWLEDGE, SKILLS AND ABILITIES

+ Strong attention to detail REQUIRED.

+ Strong organizational, data analysis and problem-solving skills REQUIRED.

+ Familiarity with statistics and statistical analysis PREFERRED.

+ Advanced knowledge of Microsoft Excel PREFERRED.

LICENSES AND CERTIFICATIONS

+ Ability to visually portray data PREFERRED.

The University of Rochester is committed to fostering, cultivating, and preserving an inclusive and welcoming culture to advance the University’s Mission to Learn, Discover, Heal, Create – and Make the World Ever Better. In support of our values and those of our society, the University is committed to not discriminating on the basis of age, color, disability, ethnicity, gender identity or expression, genetic information, marital status, military/veteran status, national origin, race, religion, creed, sex, sexual orientation, citizenship status, or any other characteristic protected by federal, state, or local law (Protected Characteristics). This commitment extends to non-discrimination in the administration of our policies, admissions, employment, access, and recruitment of candidates, for all persons consistent with our values and based on applicable law.

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Learn. Discover. Heal. Create.

Located in western New York, Rochester is our namesake and our home. One of the world’s leading research universities, Rochester has a long tradition of breaking boundaries—always pushing and questioning, learning and unlearning. We transform ideas into enterprises that create value and make the world ever better.

If you’re looking for a career in higher education or health care, the University of Rochester may offer the perfect opportunity for your background and goals

At the University of Rochester, we are committed to fostering, cultivating, and preserving an inclusive and welcoming culture and are united by a strong commitment to be ever better—Meliora. It is an ideal that informs our shared mission to ensure all members of our community feel safe, respected, included, and valued.