Boehringer Ingelheim Jobs

Description

The AI and Digital Innovation group within the Nonclinical Drug Safety (NDS) department at Boehringer Ingelheim is seeking a highly motivated and talented Computational Toxicologist/biologist to join our Computational Toxicology team in Ridgefield, CT. The primary function of this team is to provide in silico-based support for drug safety decisions. The successful candidate will have a passion for using advanced data science, including artificial intelligence (AI) and machine learning (ML)-based approaches, to inform drug development and safety. This Senior Principal Scientist will leverage AI/ML and other computational tools to access and gain insights into next-generation toxicity information and help develop a data management framework to enhance toxicology assessments. The candidate will be expected to present and publish research findings both internally and externally and to collaborate broadly with colleagues in iTox laboratories, Experimental Pathology, NDS Strategies, and global Computational Biology groups within Discovery Research.

As an employee of Boehringer Ingelheim, you will actively contribute to the discovery, development, and delivery of our products to our patients and customers. Our global presence provides opportunity for all employees to collaborate internationally, offering visibility and opportunity to directly contribute to the success of the company. We realize that our strength and competitive advantage lie with our people. We support our employees in a number of ways to foster a healthy working environment, meaningful work, diversity and inclusion, mobility, networking, and work-life balance. Our competitive compensation and benefit programs reflect Boehringer Ingelheim's high regard for our employees.

Duties & Responsibilities

• Lead and Leverage the power of AI/ML algorithms to develop comprehensive predictive toxicology models for various endpoints (e.g., Immunotoxicity, organ-specific toxicity) for new biological entities (NBEs). These models incorporate diverse data types such as in-vitro/in-vivo data, multi-omics data, text-based data, and image data.

• Design and implement innovative system toxicology approaches, including network toxicology based on deep learning. These methods integrate diverse biological and toxicological profiles using both internal and external toxicology-related databases and resources.

• Employ standardized pipelines to analyze biological data from various technologies, specifically for AI/ML data curation and processing purposes.

• Work closely with other functions within Global NDS, including Project Team Toxicologists, and support project teams as a computational expert for the identification of toxicological liabilities of drug candidates.

• Actively lead and participate in and contribute to research collaborations with external stakeholders, focusing on developing innovative AI/ML solutions to augment drug safety evaluation.

• Communicate with clarity the predicted toxicological implications of models/analytics in presentations to key stakeholders.

Requirements

• Ph.D. degree from an accredited institution with at least 7 years experience in Computational Biology, Toxicology, Bioinformatics, Computer Science, Data Science, or a related scientific field.

• Demonstrated experience with advanced AI/ML techniques, including generative models like Generative Adversarial Networks (GANs), Stable Diffusion, deep learning models such as Deep nuero netwrorks (DNN), Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs).

• Proficiency in Python and other-related languanges, the primary languages used for machine learning and deep learning tasks.

• Understanding of processing and analyzing various types of biomedical data, such as genomics data, Standard for Exchange of Nonclinical Data (SEND) data, molecular data, or imaging data. Familiarity with relevant data formats and preprocessing techniques.

• A firm understanding and hands-on experience with deep learning frameworks such as TensorFlow or PyTorch.

• Ability to analyze and interpret extensive datasets within the pharmaceutical domain, using tools such as Python, R, or SQL. Proficiency in creating visually engaging and informative data visualizations using libraries like ggplot, Matplotlib, Seaborn, or Tableau.

• Familiarity with cloud platforms like Azure and AWS, and understanding of distributed computing frameworks. Excellent communication skills to articulate complex technical concepts and results effectively to both technical and non-technical stakeholders, alongside the ability to meticulously document code and processes.

• Understanding of toxicology, pharmacology, or drug development processes is a big plus but not necessary.

• Previous experience working in a fast-paced matrixed environment (highly preferred).

Eligibility Requirements:

• Must be legally authorized to work in the United States without restriction.

• Must be willing to take a drug test and post-offer physical (if required)

• Must be 18 years of age or older

Compensation data

This position offers a base salary typically between $135,000 and $232,000.  The position may be eligible for a role specific variable or performance-based bonus and or other compensation elements.  For an overview of our benefits please click here. (https://www.boehringer-ingelheim.com/us/careers/benefits-rewards) ​

All qualified applicants will receive consideration for employment without regard to a person’s actual or perceived race, including natural hairstyles, hair texture and protective hairstyles; color; creed; religion; national origin; age; ancestry; citizenship status, marital status; gender, gender identity or expression; sexual orientation, mental, physical or intellectual disability, veteran status; pregnancy, childbirth or related medical condition; genetic information (including the refusal to submit to genetic testing) or any other class or characteristic protected by applicable law.