Preclinical R&D Scientist - Drug Development

Mercor

Berlin

Vor Ort

EUR 83.000 - 124.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

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Zusammenfassung

Mercor is seeking a hands-on preclinical R&D specialist to help guide AI-driven drug discovery. You will blend bench experience with translational insight to train models using real-world pharma data.

This ongoing, part-time engagement (~10 hours/week) is ideal for experts who have taken drug programs from bench to clinic and can advise on target selection, modality considerations, and data quality standards within a cutting-edge AI platform.

Qualifikationen

  • Hands-on preclinical R&D experience at a company developing its own drug assets.
  • Experience across discovery biology, pharmacology, toxicology, or translational sciences is a must.
  • Experience taking programs toward clinic is highly desirable.

Aufgaben

  • Review technical materials and real-world R&D data to inform model development.
  • Label, classify, and annotate data and model outputs for training.
  • Provide expert input on target/modality selection and risk trade-offs.
  • Help define data structure and quality standards for the dataset pipeline.
  • Participate in client discussions and research engagements.

Kenntnisse

Preclinical R&D experience
Drug modalities knowledge
Data labeling/annotation
Translational biology
IND-enabling experience

Jobbeschreibung

Mercor is partnering with a venture-backed AI lab building frontier AI platforms and physics-based foundation models for chemistry, materials science, and drug discovery. They're extending their platform into new areas of pharmaceutical development and are looking for hands-on preclinical R&D experts across drug modalities to help guide what they build.

Are you a preclinical R&D scientist who has taken drug programs from the bench toward the clinic - and curious how AI is reshaping drug discovery? This is a hands-on role that blends your wet-lab and translational experience with a growing understanding of how scientific data trains the next generation of AI models.

In this role, you'll:
  • Review technical materials and real-world R&D data in your area of expertise
  • Label, classify, and annotate scientific data and model outputs to improve model performance
  • Provide expert perspective on key scientific and development decisions (target/modality selection, optimization, trade-offs, risk)
  • Help define structure and quality standards for the client's dataset pipeline
  • Participate in expert discussions, interviews, and research engagements
You're a strong fit if you:
  • Have hands-on, non-administrative preclinical R&D experience at a company that develops its own drug assets in-house and has taken programs to the clinic - Must Have
  • Work in a core R&D function: discovery biology, medicinal chemistry, protein/antibody engineering, computational, in vivo/translational, pharmacology/PK-PD, toxicology, or CMC/formulation - Must Have
  • Have hands-on experience with one or more drug modalities (small molecules, monoclonal antibodies, peptides, ADCs, bispecifics, mRNA, siRNA, ASOs, PROTACs, molecular glues, cell therapies, gene therapies, radioligand therapies, etc.) - Must Have
  • Have 5+ years of relevant industry R&D experience (flexible based on depth)
  • Have taken a program through lead optimization or IND-enabling/preclinical development (nice to have)
  • Have experience at mid-sized, emerging, or resource-constrained biotech - ideally currently outside the top-20 pharmaceutical companies (nice to have)

This is a hands-on preclinical R&D role - likely not the right fit if your work is mainly CRO/CDMO services, academic-only, QC/analytical-only, clinical-development-only, diagnostics, or regulatory/medical-writing.

Your work will directly feed into the models reshaping how medicines are discovered, helping intelligent systems reason about real-world pharmaceutical R&D.

Here are more details about the role:
  • You will interface directly with the client team.
  • This is an ongoing, part-time engagement of roughly 10 hours per week.
  • Seniority welcome from individual contributor through Director.
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