Senior Research Scientist III, Computational Biology & Toxicology

The Computational Toxicology group is dedicated to advancing in-silico approaches that improve the prediction and mechanistic understanding of drug safety across small molecules biologics and emerging modalities. This role sits at the intersection of biological science and computational innovation and that intersection is intentional.

We are looking for a scientist with deep domain knowledge in biology who has also developed computational skills to independently design build and deploy data-driven solutions. The ideal candidate can stand at the bench conceptually understand what drives experimental variability and architect computational solutions that reflect biological reality.

The role focuses on integrating diverse data sources including pharmacology toxicology genomics pathology chemistry and clinical datasets into predictive and interpretable models. You will work directly with research scientists to understand their workflows co-design solutions and build tools that make computational capabilities accessible to generalist scientists across Development Sciences.

Responsibilities

• Serve as a scientific translator between wet-lab researchers and computational infrastructure understanding experimental design data provenance and biological context well enough to ensure fit-for-purpose solutions
• Engage directly with scientists to understand existing laboratory and analytical workflows identify bottlenecks and co-design computational solutions that are practical reproducible and scalable.
• Develop user-friendly tools pipelines and applications designed for scientists without a computational background enabling broader Development Sciences teams to leverage computational insights
• Partner with research scientists data scientists and safety experts to design implement and validate machine learning/AI strategies that address key discovery and preclinical safety questions.
• Curate harmonize and integrate multi-modal datasets including chemical genomic molecular in vitro pathology and clinical sources into scalable workflows that support safety insight generation and risk prediction
• Translate computational findings into predictive models analytical tools and user-friendly applications that support decision-making in drug discovery and development.

Clearly communicate methods and results to multidisciplinary stakeholders tailoring messages for both technical and non-technical audiences

Qualifications :

• Senior Scientist I Qualifications: Bachelors Degree and typically 10 years of experience OR Masters Degree and typically 8 years of experience OR PhD and no experience necessary.
• Senior Scientist II Qualifications: Bachelors Degree and typically 12 years of experience OR Masters Degree and typically 10 years of experience OR PhD and 4 years of experience
• PhD in Computational Biology Biology Pharmacology Biochemistry or a related life science field with meaningful exposure to computational methods through coursework dissertation research or applied experience. Postdoctoral or industry experience preferred
• A genuine scientific foundation in biology whether through formal training research experience or applied industry work sufficient to critically evaluate experimental data identify biological confounders and contextualize computational outputs in mechanistic terms.
• Scientific coding fluency in Python (preferred) or R. We do not expect a software engineering background we expect the ability to write clean functional reproducible code in service of scientific questions.
• Working knowledge of machine learning applied to biological or safety datasets with the ability to select and justify methods based on scientific context not just algorithmic performance.
• Strong foundation in statistical and applied analytical methods including hypothesis testing Bayesian inference regression multivariate and time-series analyses.
• Expertise in advanced machine learning including deep learning supervised/unsupervised clustering and classification algorithms (e.g. SVMs random forests gradient boosting).
• Demonstrated ability to communicate computational approaches and results to non-computational scientists including presenting analytical strategies and translating findings into actionable scientific insights.

• Preferred

• Demonstrated experience working with pathology and/or safety datasets; familiarity with integrating histopathology clinical pathology or safety study data into computational workflows.
• Hands-on wet lab experience (e.g. experimental design assay development or mechanistic biology studies) that informs a deeper understanding of data generation variability and biological constraints.
• Experience with scalable computing (parallelization cloud platforms) and database querying for large biological datasets.
• Experience with generative AI (GANs VAEs) or large language models (LLMs) in a scientific context.
• Experience in data visualization and interface development with an emphasis on presenting biological and safety-related data intuitively for non-technical users.

Additional Information :

Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: 

• The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location and we may ultimately pay more or less than the posted range. This range may be modified in the future. 

• We offer a comprehensive package of benefits including paid time off (vacation holidays sick) medical/dental/vision insurance and 401(k) to eligible employees.

• This job is eligible to participate in our long-term incentive programs. 

Note: No amount of pay is considered to be wages or compensation until such amount is earned vested and determinable. The amount and availability of any bonus commission incentive benefits or any other form of compensation and benefits that are allocable to a particular employee remains in the Companys sole and absolute discretion unless and until paid and may be modified at the Companys sole and absolute discretion consistent with applicable law.

AbbVie is an equal opportunity employer and is committed to operating with integrity driving innovation transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled. 

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Work :

No

Employment Type :

Full-time