Data Quality & Selection for Biological Foundation Models

Inceptive; Palo Alto (CA); On-site; USD 140,000 - 220,000; Full time

Job summary

Inceptive in Palo Alto is seeking a PhD-level computational biology expert to help pioneer AI-driven drug design. You will design and analyze large-scale biological experiments that power machine learning models, and you will collaborate with biologists and ML researchers across US and Europe.

You will translate experimental insights into scalable data-generation strategies, assess assay quality, and communicate findings to engineering and scientific teams.

Qualifications

• PhD in computational biology, systems biology, genomics, bioengineering, biostatistics, biophysics, or a related quantitative discipline, or equivalent practical experience.
• Demonstrated track record of analyzing complex biological datasets and translating computational insights into experimental validation or new data collection.
• Strong foundation in experimental design, statistical analysis, and quantitative reasoning.
• Deep understanding of sources of experimental variability, batch effects, and assay artifacts in biological data.
• Capable programmer in Python and common scientific computing libraries.
• Excellent written and verbal communication skills, including the ability to communicate effectively across computational and experimental disciplines.
• Availability to work with team members across US and Europe, with meetings starting at 8am PT and ending at 7pm CET. Readiness to travel several times a year for company retreats and business events.
• We value the benefits of in-person collaboration and expect candidates to primarily work from our office location.

Responsibilities

• Embody our vision of an antedisciplinary environment and embrace learning about areas outside of your traditional area of expertise.
• Develop statistical and computational approaches to characterize assay quality, reproducibility, and sources of experimental variation.
• Identify and investigate sources of bias and measurement artifacts in biological data.
• Design and analyze large-scale biological experiments that generate training and evaluation data for machine learning models.
• Partner with experimental scientists to improve assay design, controls, and data collection strategies.
• Collaborate with machine learning researchers to understand how experimental design decisions impact model training and evaluation.
• Analyze, visualize, and communicate findings to support decision-making across scientific and engineering teams.

Skills

Python

Statistical analysis

Experimental design

Data analysis

Biology knowledge

Education

PhD in computational biology

Tools

R

NumPy/SciPy

Job description

Inceptive in Palo Alto is seeking a PhD-level computational biology expert to help pioneer AI-driven drug design. You will design and analyze large-scale biological experiments that power machine learning models, and you will collaborate with biologists and ML researchers across US and Europe.

You will translate experimental insights into scalable data-generation strategies, assess assay quality, and communicate findings to engineering and scientific teams.