Head of Data Science(Principal Investigator)

Lifeline AI is a pioneer in transforming medicine by addressing the limitations of traditional AI in therapeutic discovery with its innovative "glass box" solution. Our safety-first AI engine ensures that generative molecular designs adhere to strict biological and physical constraints, offering scientific legitimacy and a transparent audit trail for every prediction.
Our core platform, the Personalized Health Operating System (PH-OS), is a safety-first AI engine that validates generative molecular designs against strict biological and physical constraints. Unlike standard models that merely predict plausibility, our system enforces scientific validity—identifying root causes rather than addressing symptoms. We are on a mission to shift healthcare from reactive treatments to proactive, personalized therapeutic generation.
The Opportunity
You will be working directly on beyond state-of-the-art infrastructure designed to disrupt the healthcare sector. We are seeking an elite, high-level scientific and computational expert to serve as our Senior Computational Chemist/Physicist reporting directly to the Chief Executive Officer (CEO). In this role, you will be expected to provide high-level scientific and computational expertise, directly responsible for scaling our foundational computational architectures.
Currently, this role offers significant equity compensation only, with a transition to a competitive market salary contingent upon securing our initial seed funding or grant awards. You will be directly instrumental in unlocking this capital. This is a high-risk, high-reward opportunity for a visionary PhD/MD who wants to own a substantial piece of the "Glass Box" revolution in medicine.
The Role
This is a full-time remote role for a Lead Computational Physicist specializing in Tensor Networks and High-Performance Computing (HPC). The role involves leading research and development efforts, specifically modeling complex physical and biological systems using advanced computational physics techniques. The candidate will design, optimize, and validate algorithms for tensor network simulations applied to biological problems and utilize HPC architectures to ensure scalability. Collaborative problem-solving with interdisciplinary teams and contributing to scientific advancements in personalized healthcare are integral aspects of the position. In addition, you will also act as a key ambassador and the Principal Scientific Investigator, taking existing computational architectures and making it universal, optimizing for production grade deployment. to ensure our core mathematical engine is flawless, scalable, and capable of modeling highly complex physical and biological systems without compromise.
You will act as the bridge between computational physics, deterministic mathematics, and real-world software engineering—optimizing orchestrating complex cloud deployments, and full-stack application development.
Who You Are
Expertise in Computational Physics, Chemistry, Tensor Networks, and High-Performance Computing
Multi-Disciplinary Engineer: You are fundamentally a world-class software and systems engineer, but you have a deep specialization in Machine Learning Operations (MLOps) and infrastructure.
You have deep expertise in Python, PyTorch, and CUDA. You understand how memory is allocated and know how to squeeze every drop of performance out of high-end hardware.
Scientifically Fluent: You are completely unfazed by scientific computing libraries (e.g., SciPy, RDKit, OpenMM) and possess strong linear algebra fundamentals.
Key Responsibilities:
Own the Architecture: Design, deploy, and maintain fault-tolerant, scalable cloud infrastructure on Multi-Cloud Platforms.
Optimize the Engines: Manage GPU VRAM, optimize PyTorch executions, and refine scripts to bypass standard software bottlenecks for maximum computational efficiency.
Deploy & Connect: Manage API deployments (e.g., FastAPI) to seamlessly route complex back-end data workflows to front-end mockups and user interfaces.
Debug & Validate: Act as the final line of defense, validating, testing, and hardening algorithmic scripts co-developed alongside advanced AI coding tools.
Mathematical Auditing: Review and optimize complex Python scripts simulating potential energy surfaces, ensuring strict thermodynamic invariants are maintained.
Tensor Network Optimization: Implement and scale out-of-core tensor network contractions (using libraries like cuTensorNet or JAX) across distributed architectures without triggering Volatile Random-Access Memory (VRAM) exhaustion.
Numerical Stability & Error Mitigation: Engineer robust mitigations for catastrophic cancellation and floating-point rounding errors in high-order finite difference calculations.
Technical Validation: Serve as the final authority on scientific code integrity; you will be responsible for peer-reviewing the team's scripts to ensure that AI-generated hypotheses are computationally sound and biologically plausible.
Grant-to-Code Alignment: Translate high-level grant objectives (NIH/NSF) into specific technical milestones for the engineering team, ensuring that our "Glass Box" deliverables meet the rigorous standards of federal auditors.
Hands-on PI Leadership: While this is a leadership role, you must be willing to "look under the hood" of our PH-OS to verify that the causal AI engine is correctly interpreting multi-omic interactions.
Audit and validate Python/R scripts to ensure algorithmic outputs align with biological ground truths.
Scientific Leadership: Advanced degree (PhD or MD required) in computational biology, bioinformatics, biomedical engineering, or a related field.
Communication: Exceptional ability to articulate complex scientific concepts to both grant committees and non-technical stakeholders.
Tech-Forward Mindset: Deep understanding of AI applications in healthcare, specifically Causal AI and Multi-Omics.
Strategic Vision: Experience moving a product from "Pre-Clinical Feedback" to commercial viability.
Strong analytical skills: for scientific research, data analysis, and problem-solving
Exceptional communication skills, with the ability to articulate complex concepts to diverse audiences
Proven expertise and experience: in leading and conducting innovative research
Track record of leadership in interdisciplinary teams and successfully managing projects
Qualifications
Expertise in Computational full stack custom development architecture, and deployment. (Computational Physics Engines, Tensor Networks, and High-Performance Computing)
Strong background in application development and First-Principle Medical Physics
Deep theoretical and applied understanding of Tensor Network States, and Deep-Neural Networks.
Proficient in Radiation Physics and its computational applications
Experience in Research and Development (R&D), particularly in computational and scientific innovations
Mastery in scientific programming languages (e.g., JAX, PyTorch, CUDA, Python, C++, Fortran) and familiarity with HPC environments
Ph.D. or post grad experience in Quantum Physics, Applied Mathematics, Quantum Information Science, Theoretical Computer Science, or a closely related field.Physics, Computational Biology, Applied Mathematics, or a related field
Quantum Expertise: Deep theoretical understanding of quantum mechanics, quantum open systems, and quantum complexity theory.
Mathematical Proficiency: Exceptional grasp of linear algebra, probability theory, tensor networks, and group theory.
Analytical Thinking: Demonstrated ability to translate highly abstract mathematical concepts into workable computational models.
Strong analytical and problem-solving skills with the ability to work collaboratively in interdisciplinary teams
Expertise in Science and Physics with a strong foundation in computational or biological sciences.
Proven experience in academic environments such as University Teaching, with the ability to mentor and lead cross-functional teams.
Exceptional skills in Research with a track record of impactful publications or scientific contributions.
Strong Project Management skills, including leadership, coordination of projects, and ability to meet objectives in high-stakes environments.
Excellent communication skills and ability to translate complex scientific concepts for diverse audiences.
Ideal skills
Programming: Python (SciKit Learn, Pandas, OpenMM, NumPy, SciPy, TensorFlow), R, Matlab, shell scripting
Servers: AlphaFold/OpenFold, NVIDIA BioNeMo, Llayma
Cloud Computing: Google GCP, AWS, Azure,
Operating Systems: Windows, Linux, MacOS, Android
Other: GitHub, Docker, PyTorch, TensorFlow scientific computing libraries (e.g., SciPy, RDKit, OpenMM/QM) and possess strong mathematical fundamentals.
Data Types: NGS, DNAseq, RNAseq, CHiPseq, TCRseq, single-cell, spatial-omics, medical imaging, proteomics, TCRseq
Bioinformatics tools: GATK, Seurat, Nextflow, pathway analysis, network analysis, variant calling,
sequence alignment
Technical Skills: multi-omics data integration, systems biology modeling, single cell analysis, spatial
transcriptomics, experimental design, organoids culture, micro-fluidics, machine learning, deep learning,
large sequencing data processing, research software development, lo

Work arrangement
Yes