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Bioinformatics Associate Jobs in Coraopolis, PA (NOW HIRING)

Bioinformatics Associate information

See Coraopolis, PA salary details

$46.7K

$194K

$381.5K

How much do bioinformatics associate jobs pay per year?

As of Sep 5, 2026, the average yearly pay for bioinformatics associate in Coraopolis, PA is $194,037.00, according to ZipRecruiter salary data. Most workers in this role earn between $74,900.00 and $381,500.00 per year, depending on experience, location, and employer.

What does a Bioinformatics Associate do?

The role of a bioinformatics associate is to perform detailed data analysis in a biology or life sciences research lab. An associate is a staff scientist or researcher, and they have significant responsibilities within the lab structure. They are responsible for conducting information support using primary research as well as developing models using a data algorithm or other analytical tools. A bioinformatics associate uses these to analyze the information and data sets collected in the lab. They may also develop a storage and archiving system so that other researchers can access data sets. Qualifications to become a bioinformatics associate typically include a master’s degree or Ph.D.

What does a Bioinformatics Associate do?

A Bioinformatics Associate is responsible for analyzing and interpreting complex biological data, often using computational tools and software. They work closely with scientists to manage and process large datasets, such as genomic sequences or protein structures. Their tasks may include developing workflows, running bioinformatics pipelines, and helping to visualize and present results. Typically, they support research projects in fields like genomics, molecular biology, and drug development. Bioinformatics Associates play a key role in translating raw biological data into actionable scientific insights.

What are the key skills and qualifications needed to thrive as a Bioinformatics Associate?

A Bioinformatics Associate requires a strong background in biology, computer science, and statistics, typically supported by a relevant bachelor's or master's degree. Familiarity with bioinformatics tools such as BLAST, Python, R, and experience with genomic databases are commonly expected, along with knowledge of data visualization platforms. Critical thinking, attention to detail, and effective communication help professionals interpret complex data and collaborate with scientific teams. These skills ensure accurate analysis, meaningful insights, and successful contributions to research projects in a rapidly evolving field.

How does a Bioinformatics Associate typically collaborate with laboratory scientists and data analysts on research projects?

Bioinformatics Associates often serve as a bridge between laboratory scientists and data analysts, translating experimental requirements into computational workflows and helping to interpret complex biological data. They regularly meet with lab teams to discuss project goals, data quality, and analysis strategies, ensuring that bioinformatics approaches align with experimental designs. Collaboration is highly iterative, involving feedback loops to refine analyses based on preliminary findings and to troubleshoot data issues, which helps drive research projects forward efficiently and accurately.

What cities near Coraopolis, PA are hiring for Bioinformatics Associate jobs?

Cities near Coraopolis, PA with the most Bioinformatics Associate job openings:

Infographic showing various Bioinformatics Associate job openings in Coraopolis, PA as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 28% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $194,037 per year, or $93.3 per hour.

Post Doctoral Associate

University of Pittsburgh

Pittsburgh, PA • On-site

Full-time

Re-posted 25 days ago


Job description

Postdoctoral Associate 

Molecular/structural Biology, GPCR Biology, Organoids, RNA-seq, and AI ML /DL-driven Drug Discovery 

Recruitment focus: molecular biology, structural pharmacology by cryo-EM and X-ray crystallography, baculovirus/Sf9 expression of GPCRs, RNA-sequencing, kidney organoids, SQSTM1/p62-targeted drug MOA studies in multiple myeloma, cannabinoid receptor CB2 pharmacology, and AI/ML/DL approaches. 

Position Overview 

The Xie Laboratory at the University of Pittsburgh School of Pharmacy seeks a highly motivated Postdoctoral Associate or Lab Researcher (PhD or equivalent; exceptional MS-level candidates with relevant experience may also be considered) to join a multidisciplinary research program integrating molecular biology, structural pharmacology, receptor biology, organoid models, RNA-sequencing, and AI/ML-enabled drug discovery. The successful candidate will help advance the lab's programs centered on cannabinoid receptor CB2 signaling and pharmacology, GPCR structural biology, SQSTM1/p62-targeted small-molecule drug mechanism-of-action studies for multiple myeloma, and kidney organoid models for translational research. 

The laboratory builds on its published work in the 3D cryo-EM structure of the human CB2-Gi signaling complex (Cell, 2020; PMID: 32004460) and generative AI modeling for drug design and discovery (Cells, 2022; PMID: 35269537). More information about the lab is available at http://www.cbligand.org/XieLab. CBIDDell22.pharmacy.pitt.edu

Ideal Candidate Profile (in one of the fields) 

         Strong training in molecular biology, biochemistry, biophysics, pharmacology, structural biology, bioinformatics, computational biology, AI/data science, or a closely related field. 

         Hands-on experience with GPCR biology, receptor pharmacology, protein expression & purification, and cell-based functional assays is highly desirable. 

         Experience in human organoid and disease-model research, for example in kidney or oncology organoid model development and translational pharmacology. 

         Experience with cryo-electron microscopy, X-ray crystallography, or integrative structural pharmacology approaches is strongly preferred. 

         Experience with baculovirus/Sf9 expression systems for GPCRs or other membrane proteins is a major advantage. 

         Interest or experience in RNA-sequencing, single-cell or bulk transcriptomics, pathway analysis, and bioinformatics-driven mechanism-of-action studies is desirable. 

         Interest or experience in human kidney organoids, disease modeling, fibrosis biology, or target-specific drug MOA validation is a plus. 

         Ability to work independently while contributing effectively to a multidisciplinary team spanning experimental biology, computational modeling, and translational drug discovery. 

Key Responsibilities 

         Molecular biology and cell signaling: Design and execute experiments involving cloning, site-directed mutagenesis, CRISPR/Cas9-based approaches, receptor signaling assays, binding assays, and cellular functional assays. 

         Structural pharmacology: Support structural studies of GPCRs and signaling complexes using cryo-EM, X-ray crystallography, biochemical characterization, and structure-guided pharmacology. 

         GPCR expression and purification: Develop and optimize baculovirus/Sf9 expression, membrane protein production, purification workflows, and quality-control assays for cannabinoid receptor CB2 and related GPCR targets. 

         Human organoid and disease-model research: Contribute to kidney or oncology organoid model development and target-specific drug MOA studies relevant to fibrosis oncology translational pharmacology. 

         Hematological malignancy drug MOA: Investigate SQSTM-1/p62-targeted small-molecule or antibody autophagy cell data, decision and cell signaling studies for mechanisms of action in acute myeloid leukemia (AML), multiple myeloma (MM), kidney fibrosis, Alzheimer's disease, hematopoietic stem cells, and osteoporosis by using molecular, cellular, and omics-based approaches. 

         RNA-seq and bioinformatics: Generate, analyze, and interpret bulk, single-cell, single-nucleus, or network RNA-seq data to define drug response, pathway modulation, and disease-relevant mechanisms. 

         AI/ML/DL and computational drug discovery: Collaborate on AI, machine learning, deep learning, chemogenomics, graph neural networks, generative modeling, and structure-based drug-discovery workflows. 

         Candidates with Web/mobile app development, data analytics, network information security, GUI design, proficiency in at least one object-oriented programming language (e.g., Java, C , or C#), and scripting language (e.g., Python, PHP) will also be considered 

         Communication and mentorship: Prepare manuscripts, grant materials, presentations, and research reports; maintain organized records; and assist the PI in mentoring graduate students and junior lab researchers. 

Required and Preferred Qualifications 

         PhD or equivalent experience in molecular biology, biochemistry, biophysics, pharmacology, structural biology, bioinformatics, computational biology, AI/data science, computer science, or a related field. 

         Demonstrated ability to conduct independent and innovative research, analyze data rigorously, and communicate findings clearly in written and oral formats. 

         Strong scientific writing skills, attention to detail, and ability to prepare manuscripts, grant-related materials, and technical reports. 

         Experience with BSL2 or BSL2 cell culture, receptor pharmacology assays, protein-expression systems, or omics data analysis is preferred. 

         Experience with Python, R, molecular modeling, structural analysis, or AI/ML/DL workflows is a plus. 

         A collaborative mindset and strong interpersonal skills for working in an interdisciplinary academic and translational research environment. 

Research Areas 

The candidate may contribute to one or more of the following programs: CB2 receptor pharmacology and signaling; GPCR structural biology and ligand discovery; SQSTM1/p62-targeted drug MOA studies for AML and MM/RRMM; kidney organoid model development for drug validation; RNA-seq and pathway analysis; and AI/ML/DL-enabled drug design and translational pharmacology. 

Application Process 

Salary is commensurate with experience. Applicants should apply at www.join.pitt.edu through the Pitt Talent Center for Post-Doctoral Associates, requisition number 26004521 and include: i) a cover letter, CV, and three references; and ii) a summary of past research accomplishments and future research interests/plans.