Computational Scientist

BEPC Inc. - Business Excellence Professional Consulting; South San Francisco (CA); Sur place; USD 66 000 - 73 000; Plein temps

Avantages offerts par ce poste

Medical Insurance

Dental Insurance

Vision Insurance

Life Insurance

Résumé du poste

The BEPC Inc. - Business Excellence Professional Consulting team in South San Francisco, CA seeks a Computational Scientist to advance deep learning on large multimodal biological datasets.

The role focuses on training and evaluating models with PyTorch, designing controlled experiments, and collaborating with project leads. Strong Python, statistics, and SLURM HPC experience are required. This 12-month W2 contract offers onsite work and comprehensive benefits.

Qualifications

• PhD in a computational discipline or equivalent research experience.
• Academic background in Computational Biology, Computational Science, Statistics, Machine Learning, or a related field.
• Demonstrated experience training and evaluating deep learning models using PyTorch.
• Hands-on experience designing and executing controlled train/test split experiments.
• Experience running machine learning workloads on SLURM-based computing clusters.
• Strong knowledge of applied statistics, statistical modeling, and experimental analysis.
• Advanced proficiency in scientific Python, including NumPy, Scanpy, AnnData.

Responsabilités

• Train, evaluate, and optimize deep learning models using PyTorch on large-scale multimodal biological datasets.
• Design and execute controlled training and testing experiments to assess model performance.
• Analyze how different subsets of multimodal perturbation datasets influence model learning and predictive accuracy.
• Evaluate model predictions and outputs against experimental biological data.
• Conduct statistical analyses to interpret model performance, identify patterns, and validate findings.
• Develop and maintain reproducible scientific analysis workflows using Python, NumPy, pandas, Scanpy, and AnnData.
• Execute computational experiments using SLURM clusters and high-performance computing resources.
• Document experimental methods, analysis pipelines, model evaluations, and research findings.
• Collaborate directly with the project lead to meet research milestones and deliverables.
• Leverage established computational pipelines and analysis codebases to accelerate research.
• Communicate technical findings and recommendations to computational scientists and cross-functional research teams.

Connaissances

PyTorch

Python

Statistics

SLURM

Formation

PhD in Computational Discipline

Outils

NumPy

Scanpy

AnnData

Description du poste

Employment Type: W2 Contract – 12 Months with Possibility for Extensions

Pay Rate: $48.00–$52.88/hour – Based on experience (Paid Weekly)

Work Model: 100% Onsite

Benefits: Medical, Dental, Vision, and Life Insurance

Note: This is a W2 only role — C2C and C2H will not be considered.

Role Overview

BEPC is seeking a highly skilled Computational Scientist to support our client's cutting-edge computational biology and machine learning research in South San Francisco, CA.

This position focuses on deep learning, multimodal biological data analysis, and predictive modeling to understand how different portions of large-scale perturbation datasets contribute to machine learning model performance.

The ideal candidate has a PhD in a computational discipline or equivalent research experience, with strong hands‑on expertise in PyTorch, scientific Python, applied statistics, and SLURM-based high-performance computing.

This role offers ownership of a clearly defined research workstream, direct collaboration with the project lead, and access to an established analysis codebase and computational infrastructure.

Key Responsibilities

• Train, evaluate, and optimize deep learning models using PyTorch on large‑scale multimodal biological datasets.
• Design and execute controlled training and testing experiments to assess model performance.
• Analyze how different subsets of multimodal perturbation datasets influence model learning and predictive accuracy.
• Evaluate model predictions and outputs against experimental biological data.
• Conduct statistical analyses to interpret model performance, identify patterns, and validate findings.
• Develop and maintain reproducible scientific analysis workflows using Python, NumPy, pandas, Scanpy, and AnnData.
• Execute computational experiments using SLURM clusters and high-performance computing resources.
• Document experimental methods, analysis pipelines, model evaluations, and research findings.
• Collaborate directly with the project lead to meet research milestones and deliverables.
• Leverage established computational pipelines and analysis codebases to accelerate research.
• Communicate technical findings and recommendations to computational scientists and cross‑functional research teams.

Required Qualifications

• PhD in a computational discipline or equivalent research experience.
• Academic background in Computational Biology, Computational Science, Statistics, Machine Learning, or a related field.
• Demonstrated experience training and evaluating deep learning models using PyTorch.
• Hands‑on experience designing and executing controlled train/test split experiments.
• Experience running machine learning workloads on SLURM-based computing clusters.
• Strong knowledge of applied statistics, statistical modeling, and experimental analysis.
• Advanced proficiency in scientific Python, including:
• NumPy
• Scanpy
• AnnData
• Experience developing reproducible, well‑documented computational analyses.
• Strong analytical, problem‑solving, and scientific communication skills.
• Ability to work independently, manage research deliverables, and collaborate effectively with scientific teams.

Preferred Qualifications

• Experience analyzing single-cell transcriptomics datasets.
• Familiarity with CRISPR perturbation screens, Perturb-seq, or similar experimental approaches.
• Knowledge of representation learning and multimodal machine learning methods.
• Experience with image analysis or computational imaging.
• Background in computational genomics, systems biology, or large‑scale biological data analysis.
• Experience evaluating machine learning models against experimental biological measurements.

About BEPC

BEPC Inc., founded in 2007, is a 100% employee‑owned company providing top‑tier consulting and staffing solutions across industries like technology, engineering, manufacturing, and project management. At BEPC, we are driven by innovation and a commitment to excellence. We take pride in fostering a collaborative and innovative environment where our team members thrive. With competitive benefits, including medical, dental, vision, and life insurance, BEPC is dedicated to supporting our employees' personal and professional growth.