Entry Level Biologist Jobs
New grad biologist jobs welcome recent graduates and entry level candidates with zero to two years of experience, where strong internship work or hands-on lab coursework can matter more than a lengthy resume. Most openings are on-site roles across Consulting & Professional Services, Biotechnology & Pharmaceuticals, and Human Resources, with employers like GAP Solutions, Stantec, and Dana-Farber Cancer Institute hiring at this level now.
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Background: Multiple openings are available for highly motivated and creative postdoctoral fellows in the bioinformatics and computational biology field, to join the Xu Lab at UT Southwestern Medical Center. We are seeking a motivated bioinformatics postdoctoral fellow with interests in computational analysis of complex biological data. The successful candidate will work with diverse multi-omic datasets, develop and refine analytical pipelines, and help translate biological questions into computationally driven insights. This position offers an excellent opportunity to strengthen in-demand bioinformatics and data science skills, work in a collaborative environment with both computational and experimental researchers, and contribute to impactful publications and discoveries that support future careers in academia, industry, or biotech. Meanwhile, I also recruit new postdoc fellows on large language models (LLMs) directions. Xu lab pioneers the application of artificial intelligence (AI) — particularly foundation models and LLMs — to drive biological and medical discovery, with a focus on interpretable and generalizable AI frameworks that extend foundation models into genomics, epigenomics, and precision medicine. For example, his team developed an AI-based approach to identify cardiovascular disease genes and validated these findings experimentally in a novel mouse model and preclinical studies, leading to publication in Nature in 2020. More recently, his team developed an LLM-based method that enabled the discovery and experimental validation of a new transcriptional biosensor, published in Science in 2026. His lab has also published multiple LLM algorithms in biology and medical applications, including DEEP-Align, DeMoP, MedLLMCoach, OmniHealthFM, and others. Dr. Lin Xu has developed multiple deep learning models and statistical algorithms to identify novel disease genes and therapeutic targets [e.g., Huang et al. Nature (2020), Lu et al. Nature Machine Intelligence (2022), Chai et al. Nature Medicine (2022), Takahiko et al. Science Translational Medicine (2022) (Cover Story), Shi et al. Cancer Cell (2022), Lebek et al. Science (2023), Xu et al. Nature Communications (2023), Zhu et al. Cancer Cell (2023), Zhang et al. Journal of Clinical Investigation (2023), He et al. Nature Communications (2023), Yu et al. Nature Communications (2023), Santos et al. Nature Communications (2023), Li et al. Nature Communications (2023), Wei et al. Cell (2023), Hernandez et al. PNAS (2024), Hu L et al. Mol Cell (2024), Eglenen-Polat et al. Nature Communications (2024), Lin CC et al. Nature Communications (2024), Xu L. et al. Nature Communications (2024), Venkateswaran N. et al. Nature Communications (2024), Chen S. et al. Nature Communications (2025), Liao C, Nature Communications (2025), Yang X. et al. Nature Immunology (2025), Lu ZY. et al. Nature Communications (2025), Zhou Y. et al. Nature Communications (2025), Adachi Y et al. J Clin Invest. (2025), Napolitano F, et al. J Clin Invest. (2025), Bann et al. Circulation (2025), Ding et al. Circulation (2025), Caravia XM, et al. Proc. Natl. Acad. Sci. (2025), Guan P, et al. Proc. Natl. Acad. Sci. (2025), Engreitz JM, et al. Nature (2025), Li H et al., Science (2026)]. Since 2022, his lab’s research has been published in a series of high-impact journals, including Nature, Science, Cell, Nature Medicine, Cancer Cell, eLife, PNAS, Nature Machine Intelligence, Nature Immunology, Nature Metabolism, Nature Communications, Science Translational Medicine, Science Advances, Molecular Cell, Genes & Development, Cell Reports, Journal of Clinical Investigation, Circulation, Circulation Research, and Developmental Cell. Building on these publications in bioinformatics and AI fields, the Xu Lab has received support from multiple funding sources, including the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), National Human Genome Research Institute (NHGRI), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), Cancer Prevention and Research Institute of Texas (CPRIT), U.S. Department of Defense (DoD), Hyundai Foundation, Children’s Cancer Fund, Sam Day Foundation, Rally Foundation, and Andrew McDonough B+ Foundation. Therefore, these new openings will be supported on a multi-year basis.
Position Title: Postdoctoral fellow
Position Qualifications:
- Experience with NGS data analysis and development of customized sequencing-analysis pipelines is strongly preferred.
- Experience with Linux environments and command-line tools is required.
- Doctoral degree in bioinformatics, genetics/genomics, statistics, biostatistics, computer science, systems biology, or a related field.
- Excellent spoken and written English communication skills.
Contact: Candidates should email a CV/resume directly to: Lin Xu, Ph.D. (Lin.Xu@UTSouthwestern.edu)
Application Deadline: Open until filled; applications will be reviewed on a rolling basis.
Background: Multiple openings are available for highly motivated and creative postdoctoral fellows in the bioinformatics and computational biology field, to join the Xu Lab at UT Southwestern Medical Center. We are seeking a motivated bioinformatics postdoctoral fellow with interests in computational analysis of complex biological data. The successful candidate will work with diverse multi-omic datasets, develop and refine analytical pipelines, and help translate biological questions into computationally driven insights. This position offers an excellent opportunity to strengthen in-demand bioinformatics and data science skills, work in a collaborative environment with both computational and experimental researchers, and contribute to impactful publications and discoveries that support future careers in academia, industry, or biotech. Meanwhile, I also recruit new postdoc fellows on large language models (LLMs) directions. Xu lab pioneers the application of artificial intelligence (AI) — particularly foundation models and LLMs — to drive biological and medical discovery, with a focus on interpretable and generalizable AI frameworks that extend foundation models into genomics, epigenomics, and precision medicine. For example, his team developed an AI-based approach to identify cardiovascular disease genes and validated these findings experimentally in a novel mouse model and preclinical studies, leading to publication in Nature in 2020. More recently, his team developed an LLM-based method that enabled the discovery and experimental validation of a new transcriptional biosensor, published in Science in 2026. His lab has also published multiple LLM algorithms in biology and medical applications, including DEEP-Align, DeMoP, MedLLMCoach, OmniHealthFM, and others. Dr. Lin Xu has developed multiple deep learning models and statistical algorithms to identify novel disease genes and therapeutic targets [e.g., Huang et al. Nature (2020), Lu et al. Nature Machine Intelligence (2022), Chai et al. Nature Medicine (2022), Takahiko et al. Science Translational Medicine (2022) (Cover Story), Shi et al. Cancer Cell (2022), Lebek et al. Science (2023), Xu et al. Nature Communications (2023), Zhu et al. Cancer Cell (2023), Zhang et al. Journal of Clinical Investigation (2023), He et al. Nature Communications (2023), Yu et al. Nature Communications (2023), Santos et al. Nature Communications (2023), Li et al. Nature Communications (2023), Wei et al. Cell (2023), Hernandez et al. PNAS (2024), Hu L et al. Mol Cell (2024), Eglenen-Polat et al. Nature Communications (2024), Lin CC et al. Nature Communications (2024), Xu L. et al. Nature Communications (2024), Venkateswaran N. et al. Nature Communications (2024), Chen S. et al. Nature Communications (2025), Liao C, Nature Communications (2025), Yang X. et al. Nature Immunology (2025), Lu ZY. et al. Nature Communications (2025), Zhou Y. et al. Nature Communications (2025), Adachi Y et al. J Clin Invest. (2025), Napolitano F, et al. J Clin Invest. (2025), Bann et al. Circulation (2025), Ding et al. Circulation (2025), Caravia XM, et al. Proc. Natl. Acad. Sci. (2025), Guan P, et al. Proc. Natl. Acad. Sci. (2025), Engreitz JM, et al. Nature (2025), Li H et al., Science (2026)]. Since 2022, his lab’s research has been published in a series of high-impact journals, including Nature, Science, Cell, Nature Medicine, Cancer Cell, eLife, PNAS, Nature Machine Intelligence, Nature Immunology, Nature Metabolism, Nature Communications, Science Translational Medicine, Science Advances, Molecular Cell, Genes & Development, Cell Reports, Journal of Clinical Investigation, Circulation, Circulation Research, and Developmental Cell. Building on these publications in bioinformatics and AI fields, the Xu Lab has received support from multiple funding sources, including the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Cancer Institute (NCI), National Heart, Lung, and Blood Institute (NHLBI), National Human Genome Research Institute (NHGRI), National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), Cancer Prevention and Research Institute of Texas (CPRIT), U.S. Department of Defense (DoD), Hyundai Foundation, Children’s Cancer Fund, Sam Day Foundation, Rally Foundation, and Andrew McDonough B+ Foundation. Therefore, these new openings will be supported on a multi-year basis.
Position Title: Postdoctoral fellow
Position Qualifications:
- Experience with NGS data analysis and development of customized sequencing-analysis pipelines is strongly preferred.
- Experience with Linux environments and command-line tools is required.
- Doctoral degree in bioinformatics, genetics/genomics, statistics, biostatistics, computer science, systems biology, or a related field.
- Excellent spoken and written English communication skills.
Contact: Candidates should email a CV/resume directly to: Lin Xu, Ph.D. (Lin.Xu@UTSouthwestern.edu)
Application Deadline: Open until filled; applications will be reviewed on a rolling basis.
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Entry Level Biologist Jobs: Frequently Asked Questions
How do I get an entry level biologist job?
Start by highlighting lab skills, coursework, and any internship or research experience on your resume, even if unpaid. Employers at this level look for familiarity with standard techniques like PCR, microscopy, or data collection, along with attention to detail and a science degree. A well-documented capstone project or thesis can give you a real edge over candidates with a bare resume.
Which companies hire entry level biologists?
Companies hiring entry level biologists right now include GAP Solutions, Stantec, and Dana-Farber Cancer Institute, based on current listings on Migrate Mate as of August 2026. Hiring at this level comes from a wide range of employers, including research institutions, biotech firms, environmental consulting companies, and government agencies that regularly bring on junior candidates to support lab and field work.
Are there remote entry level biologist jobs?
Yes, though most biologist roles at this level involve on-site lab or field work. About 20% of entry level biologist openings are remote or hybrid as of August 2026, and those positions tend to focus on data analysis, scientific writing, or regulatory review rather than hands-on laboratory tasks.
Are these new grad biologist jobs?
Yes, these listings include new grad, recent graduate, and junior biologist roles. A new grad friendly posting typically welcomes candidates with zero to two years of experience and treats internships, research assistantships, or a strong portfolio as equivalent to professional work history, so you do not need a long employment record to apply and compete seriously.
Which industries hire the most entry level biologists?
Entry Level biologist roles concentrate in Consulting & Professional Services, Biotechnology & Pharmaceuticals, and Human Resources, based on current listings on Migrate Mate as of August 2026. These sectors drive junior hiring because they depend on a steady pipeline of trained scientists to support ongoing research, quality testing, environmental monitoring, and regulatory compliance work that does not require years of independent experience.