Bioinformatics Analyst (Cheminformatics)

University of Miami•Miami, FL

12d•Onsite

About The Position

The Bioinformatics Analyst works with research staff to extend capabilities in bioinformatics and improve understanding of genetic variation in human health and disease. The Bioinformatics Analyst maintains and performs analysis with existing pipelines while assisting and benchmarking the development of novel methods. The Sylvester Comprehensive Cancer Center & the Department of Molecular and Cellular Pharmacology are actively seeking a full-time Bioinformatics / Cheminformatics Analyst to work on the UHealth campus in Downtown Miami. At Sylvester, we are at the cutting edge of healthcare innovation, leveraging artificial intelligence and machine learning to transform drug discovery and development. Our mission is to accelerate the delivery of therapeutic solutions to patients through state-of-the-art technology and groundbreaking research. The Analyst will leverage expertise in computational chemistry, bioinformatics, and AI to process and analyze large-scale biomedical, small molecule bioactivity, structural biology, image, and clinicogenomic datasets, integrating them with the Sylvester Data Portal. The successful candidate will work within an interdisciplinary team of research scientists, data engineers, and full-stack developers, using state-of-the-art software development practices to enhance the university’s research activities.

Requirements

Bachelor's degree required. PhD degree in relevant field preferred
Minimum 1 year of relevant experience
Skill in collecting, organizing, and analyzing data.
Ability to recognize, analyze, and solve a variety of problems.
Ability to exercise sound judgment in making critical decisions.
Ability to process and handle confidential information with discretion.
Proficiency in computer software.
Fluency in R or Python and Unix (bash).
Experience with analyzing and interpreting different omics and/or drug discovery datasets (WES, WGS, bulk/single-cell RNA-Seq, ATAC-Seq, Drug Screening, CRISPR Screening).
Experience with using common open-source bioinformatics/NGS workflows (BWA, STAR, Picard, GATK, etc.).
Familiarity with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch), and developing and deploying machine learning models.
Highly motivated, strong work ethic, and able to work independently and with a team.
Excellent skills in communication, organization, and time management.

Nice To Haves

PhD or MSc degree in computational chemistry, computational biology, medicinal chemistry, pharmaceutical sciences, computational sciences, or a related field.
For Ph.D. holders: 0-3 years of relevant experience in computational chemistry, AI, and drug discovery.
Deep expertise with chemical toolkits such as DeepChem, ChemAxon, OEChem, or RDKit.
Familiarity with drug discovery databases (CTRP, GDSC, PRISM, CCLE, DepMap, LINCS) and publicly available clinicogenomic datasets (CPTAC, TCGA, AACR Project GENIE, etc.).
Experience with Cloud Computing Environments (e.g., Azure).
Familiarity with relational (e.g., PostgreSQL) and/or NoSQL databases (e.g., MongoDB).
Familiarity with container technologies (e.g., Docker).
Experience with Generative AI tools and techniques.
Familiarity with High Performance Computing.
Familiarity with version control (Git).

Responsibilities

Runs and maintains existing next generation data analysis pipelines.
Assists senior bioinformatics analysts in pipeline and algorithm development and validation.
Extracts features of interest from data relating to specific biological questions.
Contributes to the maintenance of genomic and clinical databases.
Performs statistical and integrative data analysis on genomics and clinical data.
Works along-side other team members and data analysts.
Follows standard operating procedures, documentation, and scripts to generate reports.
Adheres to University and unit-level policies and procedures and safeguards University assets.
Process and analyze large-scale multi-omics and drug discovery datasets (WES, WGS, bulk/single-cell RNA-Seq, ATAC-Seq, Drug Screening, CRISPR Screening).
Develop and maintain production-grade pipelines for processing and analysis of diverse biomedical datasets.
Develop visualization and bioinformatic analysis tools for exploring diverse biomedical data.
Integrate developed tools and pipelines with Sylvester’s internal end-user data analytics platform.
Apply state-of-the-art AI, bioinformatics, and biostatistics approaches to cancer precision medicine.
Write standard operating procedures and other relevant documentation.
Develop and apply AI/ML models for structure-based and ligand-based drug design.
Utilize computational tools to predict and optimize pharmacokinetic (PK) and pharmacodynamic (PD) properties of drug candidates.
Design and implement algorithms to identify novel drug candidates and elucidate their mechanisms of action.
Integrate and analyze large-scale biological, chemical, and clinical datasets to extract insights and inform drug discovery decisions.
Collaborate with cross-functional teams to advance drug discovery projects.
Analyze and interpret PK/PD data using advanced statistical and modeling software.
Stay updated with advancements in computational chemistry, AI, and bioinformatics.
Contribute to the development of new computational tools and methodologies.
Present findings to both technical and non-technical stakeholders.
Participate in scientific discussions and strategy meetings, providing AI/ML expertise.
Author scientific papers, reports, and patents related to AI/ML in drug discovery.