SI/ML Computational Biologist - Postdoctoral Researcher

Description

The company is hiring a postdoctoral researcher to work where super intelligence (SI), machine learning (ML) and computational biology meet.

You will apply and adapt current SI and ML methods to study how hosts respond in complex biological systems.

The work combines large multiomic datasets (bulk, single-cell, spatial and multimodal) from animal models and human cohorts to find molecular patterns tied to disease course, immune activity and biological resilience.

You will use deep learning, self-supervised learning and biological foundation models to produce useful biological findings and predictive models that hold across different systems.

The role sits in the Integrative Multi-Omics Group, where senior scientists guide work on large, high-dimensional biological data in a collaborative, multidisciplinary setting.

This is a two-year term, extendable to three years in total.

Responsibilities

• Build and apply ML methods for prediction and representation learning on high-dimensional biological data.
• Help design and run workflows that integrate bulk, single-cell, spatial and multimodal omics data.
• Explore and apply multimodal fusion, cross-dataset integration and transfer learning.
• Train, adapt and evaluate self-supervised and foundation models for omics data.
• Build interpretable models that connect molecular states to disease trajectories and host-response phenotypes.
• Process and analyze large sequencing and other omics datasets.
• Help plan research and carry out projects.
• Present findings at seminars, conferences and technical meetings, and publish them in peer-reviewed journals.
• Work as part of a multidisciplinary team.
• Take on other tasks as needed.

Requirements

• Eligible to access the facility under Section 3112 of the NDAA.
• PhD in computational biology, bioinformatics, computer science, statistics, data science or a closely related field.
• Solid background in machine learning, statistical modeling, computational biology or another quantitative field.
• Hands-on experience analyzing high-dimensional biological data such as genomics or transcriptomics.
• Skilled in Python and R.
• Experience with ML frameworks such as PyTorch, TensorFlow or similar.
• Comfortable with Linux/Unix and scientific computing workflows.
• Track record of rigorous research and peer-reviewed publications.
• Works well in collaborative research settings.
• Clear written and spoken communication.
• Desired: experience with deep learning or probabilistic models, such as variational autoencoders, scVI or similar methods.
• Desired: experience with single-cell, spatial and/or multimodal omics data.
• Desired: experience integrating multiomic data, including multimodal single-cell datasets.
• Desired: experience with transfer learning, domain adaptation, cross-dataset integration or batch correction.
• Desired: experience with transformers, self-supervised learning or pretrained models for biological data.
• Desired: experience training and scaling ML models on large datasets.
• Desired: interest in immunology, host-pathogen biology or disease modeling.

Conditions

Onsite role.

Temporary, mentored postdoctoral training position for early-career researchers. Applicants must have received their PhD (or equivalent doctorate) within five years of the anticipated start date.

Term of two years, extendable to a maximum of three years.

Schedules are flexible, depending on project needs.

Security clearance is listed as part of this role.

Section 3112 of the 2025 NDAA generally bars citizens of China, Russia, Iran and North Korea, unless they hold dual US citizenship or legal permanent residence, from specific non-public areas of national security or nuclear weapons facilities. These restrictions apply to this role, and candidates must be eligible to access the facility under Section 3112.

Selected external applicants must pass a post-offer, pre-employment drug test, which includes testing for marijuana because federal contractor law applies.

Under Department of Energy rules, mobile devices are restricted in Limited Areas. You may be required to work in a Limited Area where personal and lab mobile devices are not allowed, including phones, tablets, fitness devices, wireless headphones and other Bluetooth or wireless devices.

If you use a medical device that pairs with a mobile device, you must follow the mobile device rules in each Limited Area section. Sensitive Compartmented Information Facilities need separate approval. Hearing aids without wireless capability, or with wireless turned off, are allowed in Limited Areas, Secure Space and Transit/Buffer Space within buildings.

Applicant information is kept confidential under EEO guidelines.

Benefits

• Flexible benefits package.
• 401(k) plan.
• Relocation assistance.
• Education reimbursement program.