Staff Scientist

Seeking a Staff Scientist to conduct research projects and assist with research activities of the Karch Lab at Washington University School of Medicine. To apply, please contact Celeste Karch at or Jacob Marsh at

Primary Duties and Responsibilities:

  • Performs iPSC culture and conducts downstream experiments and screening assays
  • Utilizes CRISPR/Cas9 technologies to perform genomic editing
  • Optimizes various molecular biology assays to ensure consistent and reliable results
  • Works closely with project coordinators, staff scientists, trainees, and technical staff to ensure the success of projects
  • Following instructions and discussions with principal investigator, designs research protocols, including developing procedures for the collection, verification and management of data.
  • Assists with grant preparation and reporting.
  • Performs complex statistical analysis of data collected and writes interpretative reports. Verifies the correctness of the data submitted and makes recommendations based on these analyses.
  • Documents research topics and prepares and submits papers based on research work to publications and committees for publication or presentation to peers.
  • Solves practical problems relating to difficulties with equipment or test subjects. Suggest technical and procedural improvements in testing methods.
  • Conducts literature searches related to research project.

Preferred Qualifications:

  • Master’s or Ph.D. degree in field relevant to studying neurodegeneration
  • Experience with techniques in molecular biology, cell biology, and biochemistry
  • Experience with methods in cell culture and aseptic technique. iPSC culture experience is not required.
  • Possess a strong understanding of CRISPR/Cas9 genome editing system
  • Organized, independent, and self-motivated
  • Demonstrated ability to be highly productive in a fluid and collaborative work environment
  • Exceptional written and oral communication skills
  • Analytical reasoning and problem solving skills
  • Ability to analyze and interpret statistical data and to communicate data in a clear, concise manner
  • Computer literacy, including the ability to use a variety of software packages to analyze data.