锦鲤求职

埃克森美孚

Toxicology Scientist - Advanced

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岗位描述

About us

For well over a century, ExxonMobil has been at the heart of creating and growing a modern world. We embrace the power and promise of technology, pushing the boundaries of what's possible. For billions around the world, lives are better and last longer because of the innovative problem solving and reliable energy we provide. And when it comes to developing industrial solutions to reduce carbon emissions, ExxonMobil is truly the leader.

We don't stop at "good enough." We are committed to doing what's right, even if it's difficult or unpopular. We hold ourselves to high standards, challenge what's possible and invest in innovation to meet society's critical needs.

Real change begins with bold questions, drive, and ambition. Here, your talent, determination and contributions shape how far you'll go and the impact you'll make along the way.

Our future success depends on exceptional people. We invest in developing talent through meaningful work, challenging assignments, mentorship, and experiences that help build the next generation of leaders.

Our Culture

We are uniquely ExxonMobil. Integrity, care, excellence, resilience and courage, these core values determine how we work every day. At ExxonMobil, our values aren't just words— they're how we show up, focused on delivering the right answer, the right way, every day.

Job Group Capability

Research

Job Group

Research

Position Summary

We are seeking a highly motivated predictive/computational toxicologist to support the application of NAMs and computational toxicology in regulatory decision making. The successful candidate will apply in silico methods, mechanistic toxicology, and data-driven approaches to support chemical risk assessment. The role will also provide toxicological support for global chemical registrations and contribute to advancing the regulatory acceptance of predictive toxicology approaches.

Key Responsibilities

Predictive & computational toxicology

Design and oversee predictive toxicology assessments using QSAR, read-across, TTC, and other New Approach Methodologies (NAMs)

Critically evaluate model outputs, applicability domains, uncertainties, and limitations of predictive toxicology tools.

Apply mechanistic toxicology principles, AOP frameworks, and mode-of-action information to support safety evaluations.

Integrate evidence from in silico predictions, in vitro studies, high-throughput screening data, existing toxicological studies and scientific literature to support WoE assessments and IATA.

Support development and evaluation of computational toxicology approaches for complex substances

Monitor and summarize developments in computational toxicology, alternative testing strategies, machine learning applications and NGRA

Support technical advocacy activities related to the regulatory application and acceptance of predictive toxicology approaches

Regulatory toxicology & study monitoring support

Provide toxicological expertise to support global chemical registration programs, including EU REACH, UK REACH, K-REACH, TSCA, China NCR and other international frameworks

Support testing strategies, data gap analyses, studies review, data quality assessment, waiver strategies, and toxicological assessment and summaries

Develop read-across and WoE justifications to support regulatory submissions

Required Qualifications

Education

Master's or PhD candidate in one of the following disciplines:

Toxicology

Computational Toxicology

Environmental Toxicology

Environmental Science

Chemistry

Pharmaceutical Sciences

Computational Biology

Bioinformatics

Public Health

Regulatory Science

Related scientific field

Technical Skills

Strong understanding of toxicology principles and chemical risk assessment.

Practical experience with QSAR, read-across, structural alerts, TTC, NAMs, or related predictive toxicology approaches

Understanding of toxicological mechanisms, ADME processes

Familiarity with WoE and IATA concepts

Understanding of regulatory requirements for chemical registration.

Experience with scientific literature review.

Strong data analysis skills using Excel and/or statistical software.

Ability to interpret toxicological and ecotoxicological studies.

Scientific writing and documentation skills.

Language Requirements

Fluent Chinese (Mandarin).

Professional working proficiency in English (written and verbal).

Preferred Qualifications

Exposure to Graph Neural Networks, molecular descriptor generation and analysis, cheminformatics workflows, predictive modelling and data-mining approaches

Experience with OECD QSAR toolbox, VEGA, Derek Nexus, Sarah Nexus, TEST, EPISuite

Familiarity with ToxCast, Tox21, AOPs, OECD NAM guidance, NGRA

Experience with REACH, MEE Order 12, TSCA, or K-REACH submissions.

Knowledge of GHS classification and SDS preparation.

Experience with Python, R, Power BI, Spotfire, or similar analytical tools.

Publication record in toxicology, chemistry, or environmental science.

Experience working in a multinational environment.

Functional Skills

Health Hazard Assessment

Target Organ Systems

Disposition of Toxicants

Toxic Chemistries

Health & Environmental Risk Assessment

Alternate Location:

Nothing herein is intended to override the corporate separateness of local entities. Working relationships discussed herein do not necessarily represent a reporting connection, but may reflect a functional guidance, stewardship, or service relationship.

Exxon Mobil Corporation has numerous affiliates, many with names that include ExxonMobil, Exxon, Esso and Mobil. For convenience and simplicity, those terms and terms like corporation, company, our, we and its are sometimes used as abbreviated references to specific affiliates or affiliate groups. Abbreviated references describing global or regional operational organizations and global or regional business lines are also sometimes used for convenience and simplicity. Similarly, ExxonMobil has business relationships with thousands of customers, suppliers, governments, and others. For convenience and simplicity, words like venture, joint venture, partnership, co-venturer, and partner are used to indicate business relationships involving common activities and interests, and those words may not indicate precise legal relationships.

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