Post Doctoral Associate

Post Doctoral Associate Pharm-Pharmaceutical Science - Pennsylvania-Pittsburgh - (26004521) 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 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: I nvestigate SQSTM-1/p62-targeted small-molecule or antibody autophagy cell data, decision and cell signaling studies for mechanisms of action i 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 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. The University of Pittsburgh is an equal opportunity employer / disability / veteran. Assignment Category: Full-time regular Campus: Pittsburgh Child Protection Clearances: Not Applicable Required Attachments: Curriculum Vitae Optional Attachments: Letters of Recommendation, Other (see posting for additional details) Assignment Category Full-time regular PI286055587