AIML Computational Biologist Postdoctoral Researcher

We are seeking a Postdoctoral Research Staff Member to conduct research at the intersection of artificial intelligence (AI) machine learning (ML) and computational biology. The successful candidate will apply and adapt state-of-the-art AI/ML approaches to understand host-response dynamics in complex biological systems. Research will focus on integrating large-scale multiomic datasets including bulk single-cell spatial and multimodal data from animal models and human cohorts to identify molecular programs associated with disease progression immune responses and biological resilience. The candidate will leverage modern machine learning approaches including deep learning self-supervised learning and biological foundation models to generate biologically meaningful insights from diverse datasets and develop predictive models that generalize across biological systems.

This position is in the Integrative Multi-Omics Group and offers the opportunity to work under the guidance of senior scientists on high-dimensional biological data at scale in a collaborative multidisciplinary environment.

This is a two-year term appointment with the possibility of extension to a maximum of three years.

In this role you will

• Develop and apply machine learning methods for prediction and representation learning from high-dimensional biological data.
• Contribute to the design and implementation of workflows for integrative analysis of multiomic datasets (bulk single-cell spatial and multimodal).
• Investigate develop and apply approaches for multimodal data fusion cross-dataset integration and transfer learning.
• Train adapt and evaluate self-supervised and foundation models for omics data.
• Develop and apply interpretable models linking molecular states to disease trajectories and host-response phenotypes.
• Process and analyze large-scale sequencing and other omics datasets.
• Present research findings at seminars conferences and technical meetings.
• Contribute to research design and project execution.
• Collaborate in a multidisciplinary team environment.
• Publish results in peer-reviewed journals.
• Perform other duties as assigned.

Qualifications :

• PhD in Computational Biology Bioinformatics Computer Science Statistics Data Science or a related field.
• Strong background in machine learning statistical modeling computational biology or a related quantitative discipline.
• Experience analyzing high-dimensional biological data such as genomics transcriptomics or related modalities.
• Proficiency in Python and R.
• Experience with ML frameworks such as PyTorch TensorFlow or similar.
• Familiarity with Linux/Unix and scientific computing workflows.
• Demonstrated ability to conduct high-quality research and publish results in peer-reviewed journals.
• Demonstrated ability to work effectively in a collaborative research environment.
• Strong written and verbal communication skills.

Desired Qualifications

• Experience with deep learning or probabilistic modeling approaches such as variational autoencoders scVI or related methods.
• Experience with single-cell spatial and/or multimodal omics data.
• Experience with multiomic data integration including multimodal single-cell datasets.
• Experience with transfer learning domain adaptation cross-dataset integration or batch correction.
• Experience with transformers self-supervised learning or pretrained models for biological data.
• Experience training and scaling machine learning models on large datasets.
• Interest in immunology host-pathogen biology or disease modeling.

Pay: $123048 Annually

Additional Information :

#LI-Onsite

All your information will be kept confidential according to EEO guidelines.

Position Information

This is a Postdoctoral appointment with the possibility of extension to a maximum of three years open to those who have been awarded a PhD at time of hire date.

Why Lawrence Livermore National Laboratory

• Included in 2026 Best Places to Work by Glassdoor!
• Flexible Benefits Package
• 401(k)
• Relocation Assistance
• Education Reimbursement Program
• Flexible schedules (*depending on project needs)
• Our values - visit  Clearance

  None required.  However if your assignment is longer than 179 days cumulatively within a calendar year you must go through the Personal Identity Verification process.  This process includes completing an online background investigation form and receiving approval of the background check.  

  National Defense Authorization Act (NDAA)

  The 2025 National Defense Authorization Act (NDAA) Section 3112 generally prohibits citizens of China Russia Iran and North Korea without dual US citizenship or legal permanent residence from accessing specific non-public areas of national security or nuclear weapons facilities.  The restrictions of NDAA Section 3112 apply to this position.  To be qualified for this position Candidates must be eligible to access the Laboratory in compliance with Section 3112.

  Pre-Employment Drug Test

  External applicant(s) selected for this position must pass a post-offer pre-employment drug test. This includes testing for use of marijuana as Federal Law applies to us as a Federal Contractor.

  Wireless and Medical Devices

  Per the Department of Energy (DOE) Lawrence Livermore National Laboratory must meet certain restrictions with the use and/or possession of mobile devices in Limited Areas. Depending on your job duties you may be required to work in a Limited Area where you are not permitted to have a personal and/or laboratory mobile device in your possession.  This includes but not limited to cell phones tablets fitness devices wireless headphones and other Bluetooth/wireless enabled devices.  

  If you use a medical device which pairs with a mobile device you must still follow the rules concerning the mobile device in individual sections within Limited Areas.  Sensitive Compartmented Information Facilities require separate approval. Hearing aids without wireless capabilities or wireless that has been disabled are allowed in Limited Areas Secure Space and Transit/Buffer Space within buildings.

  How to identify fake job advertisements

  Please be aware of recruitment scams where people or entities are misusing the name of Lawrence Livermore National Laboratory (LLNL) to post fake job advertisements. LLNL never extends an offer without a personal interview and will never charge a fee for joining our company. All current job openings are displayed on the Career Page under Find Your Job of our website. If you have encountered a job posting or have been approached with a job offer that you suspect may be fraudulent we strongly recommend you do not respond.

  To learn more about recruitment scams:  Employment Opportunity

  We are an equal opportunity employer that is committed to providing all with a work environment free of discrimination and harassment. All qualified applicants will receive consideration for employment without regard to race color religion marital status national origin ancestry sex sexual orientation gender identity disability medical condition pregnancy protected veteran status age citizenship or any other characteristic protected by applicable laws.

  Reasonable Accommodation

  Our goal is to create an accessible and inclusive experience for all candidates applying and interviewing at the Laboratory.  If you need a reasonable accommodation during the application or the recruiting process please use our online form to submit a request. 

  California Privacy Notice

  The California Consumer Privacy Act (CCPA) grants privacy rights to all California residents. The law also entitles job applicants employees and non-employee workers to be notified of what personal information LLNL collects and for what purpose. The Employee Privacy Notice can be accessed here.

  
  

  Remote Work :

  No

  
  

  Employment Type :

  Full-time