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Mutagenesis Jobs (NOW HIRING)

Saint Louis University

Adjunct Faculty

Saint Louis, MO · On-site

This role will focus on site-directed mutagenesis and functional assays of thrombin mutants. Function Faculty - Adjunct Scheduled Weekly Hours: 31 Saint Louis University is an equal opportunity ...

Saint Louis University

Adjunct Faculty

Saint Louis, MO · On-site

This role will focus on site-directed mutagenesis and functional assays of thrombin mutants. Function Faculty - Adjunct Scheduled Weekly Hours: 31 Saint Louis University is an equal opportunity ...

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Mutagenesis information

What are the key skills and qualifications needed to thrive as a Mutagenesis Scientist, and why are they important?

To thrive as a Mutagenesis Scientist, you need a strong background in molecular biology, genetics, and laboratory techniques, typically supported by an advanced degree in biological sciences. Experience with CRISPR, site-directed mutagenesis kits, PCR, and DNA sequencing platforms is essential. Attention to detail, critical thinking, and effective teamwork are valuable soft skills in this role. These skills ensure accurate genetic modifications, reliable experimental results, and successful collaboration on research projects.

What is the difference between Mutagenesis vs Genetic Engineer?

AspectMutagenesisGenetic Engineer
Required CredentialsLaboratory skills, knowledge of molecular biology, often a bachelor's or master's degreeAdvanced degrees (Master's or PhD), expertise in genetic modification techniques
Work EnvironmentResearch labs, biotech companies, pharmaceutical labsResearch institutions, biotech firms, pharmaceutical companies
Industry UsageUsed for creating genetic variations, studying mutationsDesigning and implementing genetic modifications in organisms
Common Search/ComparisonMutagenesis vs Genetic Engineer

Mutagenesis involves inducing mutations to study gene functions or create genetic diversity, often using chemical or physical agents. Genetic engineers design and implement specific genetic modifications using advanced techniques like CRISPR. While mutagenesis is more about random mutation induction, genetic engineering focuses on precise gene editing. Both roles are essential in biotechnology and share overlapping skills, but differ in complexity and purpose.

What are some typical challenges faced by scientists working in mutagenesis, and how can they be addressed?

Scientists specializing in mutagenesis often encounter challenges such as ensuring the specificity of induced mutations and accurately screening for desired genetic changes. Maintaining the viability of organisms while introducing mutations and avoiding off-target effects are also common concerns. These issues can be addressed by carefully selecting mutagenic agents, optimizing experimental protocols, and using advanced screening techniques such as next-generation sequencing. Collaboration with bioinformatics specialists and molecular biologists is also essential to interpret results and refine approaches.

What is mutagenesis?

Mutagenesis is a process by which the genetic information of an organism is changed in a stable manner, resulting in a mutation. This can occur naturally or be induced artificially in a laboratory, often using chemicals, radiation, or genetic engineering techniques. Scientists use mutagenesis to study gene function, create genetic diversity, or develop organisms with desirable traits. In research, mutagenesis helps identify the roles of specific genes and understand the effects of genetic changes.
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Mutagenesis jobs near you
Infographic showing various Mutagenesis job openings in the United States as of May 2026, with employment types broken down into 88% Full Time, 2% Part Time, 4% Temporary, and 6% Contract. Highlights an 100% Physical job distribution.
POSTDOCTORAL RESEARCHER - McDermott Center HG&D - Seplyarskiy Lab [Req#: 911441, Position#: 127940]

POSTDOCTORAL RESEARCHER - McDermott Center HG&D - Seplyarskiy Lab [Req#: 911441, Position#: 127940]

UT Southwestern Medical Center

Dallas, TX • On-site

$114K/yr

Full-time

Posted 5 days ago

UT Southwestern rating

7.8

Company rating: 7.8 out of 10

Based on 146 frontline employees who took The Breakroom Quiz

102nd of 865 rated healthcare providers

Job description

Description
Postdoctoral Researcher in Mutagenesis, Population and Statistical Genetics
A postdoctoral training opportunity is now available in the Seplyarskiy Lab in the McDermott Center for Human Growth and Development at UT Southwestern Medical Center at Dallas. We are currently accepting applications for a postdoctoral fellowship in mutagenesis, statistical genomics, and computational biology.
Research directions
  • Mutagenesis: evolution of mutational mechanisms across the tree of life; somatic mutagenesis and clonal dynamics; reconstruction of early developmental lineages from mosaic mutations.
  • Population genetics: quantifying recurrence and number of mutational origins in large cohorts; discovery of strongly selected sites and constraint from recurrence-aware models.
  • Statistical genetics: partitioning heritability and enrichment in DNA-repair and mutagenesis pathways (including cancer-relevant contexts); development of mutation rate model

Training & environment
  • Close mentorship in mutagenesis, population genetics, and statistical genetics
  • Active joint journal clubs with external groups (Ziyue Gao - UPenn, Evan Koch - Yale), collaborative community at UTSW's McDermott Center.
  • Access to large datasets (e.g., biobanks, gnomAD-class resources) and compute.

Responsibilities
  • Formulate and test new quantitative models of mutation, selection, and clonal evolution.
  • Develop methodstailored to large-scale genomic datasets.
  • Lead analyses, interpret results and drive manuscripts to completion.
  • Collaborate on related work across the lab's projects.

Qualifications
• Ph.D. (or equivalent, or soon to be completed) in Statistics, Biostatistics, Computer Science, Population/Statistical Genetics, Bioinformatics/Computational Biology
• Proficiency in R and/or Python/ or other languages
• Plus factors: experience with method development, exposure to population-genetic theory (selection, demography, coalescent/ARG), mutational-process modeling, scalable data engineering, cloud/HPC, or ancient DNA.
Application Instructions
Interested individuals should send a CV, cover letter briefly describing previous research experience, and a summary of current research interests.

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