Core Facility: Microscopy Services Laboratory

Commitment: 6 hours/week, 12 weeks

Expected Skill Development: Experience with SyGlass and full Imaris software, developing user-friendly Python tools, organizing workshops, and training researchers in software use.

Required Background or Skills: Basic experience with Jupyter notebooks and data visualization in Imaris.

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Core Facility: Research Data Management Core

Commitment: 4 hours/week, 6 weeks

Expected Skill Development: Deep understanding of NIH data management and sharing policies, data stewardship principles and tools, evaluation of data plans, packages, and repositories, hands-on experience with UNC Dataverse, and preparation for Data Steward roles.

Required Background or Skills: No specific pre-requisites.

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Core Facility: X-ray Crystallography Core Laboratory (XCL)

Commitment: 8 hours/week, 12 weeks

Expected Skill Development: MicroED skills, including micro and nanocrystal preparation, cryogenic grid handling, low dose electron diffraction, data processing, structure determination, and method optimization, along with hands-on experience operating the Talos Arctica Cryo-TEM and cross-facility collaboration, troubleshooting, and scientific communication.

Required Background or Skills: Intermediate or advanced knowledge of crystallography, basic experience operating cryo-TEM instrumentation, prior exposure to MicroED is highly desirable.

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Core Facility: GENYSIS Clinical Genomic Analysis Core

Commitment: 8 hours/week, 12 weeks (negotiable)

Expected Skill Development: Experience with methylation data from Oxford Nanopore Technology long read sequencing projects. Develop skills of building pipelines to enable large scale automation of analysis. Potentially identify a study participant’s underlying genetic condition.

Required Background or Skills: Medium to high understanding of bioinformatics and some understanding of genetics. No knowledge of methylation processes is required. Familiarity with UNC’s computing clusters Longleaf or Sycamore and experience with BASH/Linux commands is a must.

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Core Facility: GENYSIS Clinical Genomic Analysis Core

Commitment: 8 hours/week, 12 weeks (negotiable)

Expected Skill Development: Gain experience analyzing and classifying germline sequence and structural variants from rare disease genomic studies using in-house tools and public resources such as OMIM, ClinVar, ClinGen, gnomAD, and PubMed. The project can be tailored to the postdoc’s interests and experience, including work on phenotype-based variant prioritization, non-coding variants, or documentation and protocol development.

Required Background or Skills: Basic understanding of human genetics, but we are most interested in supporting a postdoc with plans to utilize their GENYSIS experience in their future career.

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Core Facility: Cryo Electron Microscopy (CryoEM) Core

Commitment: 8 hours/week, 12 weeks

Expected Skill Development: Hands-on training in cryoTEM operation, leading to independent expert-level use. Opportunity to expand an existing cryoEM or TEM skill set to include full cryoTEM operation.

Required Background or Skills: Experience in cryoEM or some experience operating of the TEM is expected. Applicants with limited experience but willing to work after hours to complete onsite training will also be considered.

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Core Facility: High Throughput Sequencing Facility (HTSF)

Commitment: 8 hours/week, 12 weeks

Expected Skill Development: Knowledge of workflows in sequencing facilities, expertise in DNA and RNA library preparation and pooling for sequencing, automated liquid handling workflows, and exposure to quality analysis for DNA and RNA sequencing data.

Required Background or Skills: Experience with library preparation for sequencing, familiarity with analysis of DNA sequencing data.

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Core Facility: Lineberger Bioinformatics Core Facility

Commitment: 8 hours/week, 12 weeks

Expected Skill Development: Experience harmonizing and standardizing multi-omics data in a high-performance computing environment using bash, Nextflow, R, and Python, with skills in quality control, reproducible research, metadata management, and hypothesis-driven analysis in large population-based cancer studies.

Required Background or Skills: Prior experience working in a Linux-based computing environment and experience using R and/or Python for data analysis. Candidates with a strong interest in computational biology, bioinformatics, or data-driven biomedical research and a willingness to self-learn new technical skills prior to and during the project will be strongly considered.

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