Sanofi

Biopharma

ScientificFellow,AI-EnabledTargetIdentification&Credentialing

€129–172k Germany FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Scientific Fellow, AI-Enabled Target Identification & Credentialing at Sanofi. Skills: AI-Enabled Target Identification, Target Credentialing, Computational Science, Scientific Strategy. Shape scientific strategy. Evaluate internal capabilities”

What You'll Achieve.

Increase probability of success

Industry & Context.

Biopharma

What They're Looking For.

Must Have

Ph.D. in computational biology, systems biology, bioinformatics, genetics, machine learning, biomedical data science, pharmacology, or a related scientific discipline, Minimum of 7 years of experience in academia, biotech, technology, or pharma, Track record in AI, computational tools, and target identification and credentialing, Demonstrated success advising senior leaders, Demonstrated success evaluating emerging scientific capabilities, Demonstrated success translating technical advances into strategic R&D impact

What You'll Do.

Shape scientific strategy

Evaluate internal capabilities

Evaluate external capabilities

Apply deep scientific judgement

Advance identification of therapeutic targets

Advance prioritization of therapeutic targets

Advance credentialing of therapeutic targets

Provide expert leadership on digital approaches

Provide expert leadership on computational approaches

Provide expert leadership on AI approaches

Accelerate target discovery

Improve target confidence

Increase probability of success

Advise senior leaders

Advise corporate management

Assess emerging methods

Assess emerging platforms

Assess emerging partnerships

Assess external innovations

Serve as internal expert consultant

Contribute deep scientific judgement

Contribute thought partnership

Establish external reputation

Maintain external reputation

Contribute to scientific community

How You'll Work.

Team & Collaboration

Across research programs; Across R&D-wide initiatives; Across a matrixed organization

Communication Scope

High-impact publications; Invited speaking engagements; Conference participation

Full Job Description

# **About _Sanofi_** We’re an R&D-driven, AI-powered biopharma company committed to improving people’s lives and delivering compelling growth. Our deep understanding of the immune system – and innovative pipeline – enables us to invent medicines and vaccines that treat and protect millions of people around the world. Together, we chase the miracles of science to improve people’s lives. # **About the** _**Job**_ Join the engine of Sanofi’s mission — where deep immunoscience meets bold, AI-powered research. In R&D, you’ll drive breakthroughs that could turn the impossible into possible for millions. **Main Responsibilities:** * The Scientific Fellow, AI-Enabled Target Identification & Credentialing, is a senior individual contributor and scientific thought leader at the intersection of AI, computational science, and target discovery. This role will shape scientific strategy, evaluate internal and external capabilities, and apply deep scientific judgement to advance the identification, prioritization, and credentialing of therapeutic targets across R&D. * The individual will provide expert leadership on how advanced digital, computational, and AI approaches can accelerate target discovery, improve target confidence, and increase probability of success. Working across research programs and R&D-wide initiatives, this person will advise senior leaders and corporate management on emerging scientific and technological advances, strategic opportunities, and differentiated approaches in AI-enabled target identification and validation. * A core expectation of the role is to help define scientific strategies and practical tactics that support company ambitions in AI-enabled target identification and credentialing. This includes assessing emerging methods, platforms, partnerships, and external innovations for scientific quality, strategic relevance, and potential impact across areas such as human genetics, multimodal data integration, causal biology, disease mechanisms, target p

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