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A biotech company is seeking a scientifically grounded expert for drug discovery to drive adoption of the Co-Folding Application among pharma R&D users. This role requires a PhD in a related field and strong user-first communication skills. Responsibilities include engaging with various stakeholders, conducting workshops, and contributing to product improvements. Competitive compensation and remote-first work environment are offered.
We are seeking a scientifically grounded expert instructor-based drug discovery with a strong user‑first, proactive mindset. This role is central to driving adoption and boosting usage of the Co‑Folding Application within leading pharma R&D organizations. You will act as a power user of Apheris products yourself, and will guide computational and medicinal chemists in benchmarking, testing, and applying our models to real programs. Your focus will be on anticipating user needs, engaging the right stakeholders, and making sure pharma scientists and users not only try the application but rely on it in their day‑to‑day work. You will collaborate closely with pharma users, internal ML scientists, the AI Applications Team, and the Product team to embed the Co‑Folding Application into existing R&D environments. If you want to accelerate the use of AI in drug discovery — and you thrive on working directly with users to ensure adoption translates into measurable value — this role is for you.
At Apheris, we power federated data networks in life sciences to address the data bottleneck in training highly performant ML models. Publicly available, molecular datasets are insufficient to train high‑quality ML models that meet industry requirements. We address this by hosting networks where pharma organizations collaboratively train higher quality models on their combined data. The Apheris product is a set of drug discovery applications enriched with the proprietary data of network participants. Our federated computing infrastructure with built‑in governance and privacy controls ensures that the data IP and ownership always stay with the data custodians.
We currently host two flagship networks: the AISB Network, focused on protein co‑folding and binding affinity prediction, and the ADMET Network, focused on small‑molecule property prediction. In addition, we have just launched our Co‑Folding Application, which enables pharma teams to deploy models like OpenFold3 and Boltz‑2 directly in their own environments — with more capabilities to follow.
Our interview process is split into three phases:
* Der Gehaltsbenchmark wird auf Basis der Zielgehälter bei führenden Unternehmen in der jeweiligen Branche ermittelt und dient Premium-Nutzer:innen als Richtlinie zur Bewertung offener Positionen und als Orientierungshilfe bei Gehaltsverhandlungen. Der Gehaltsbenchmark wird nicht direkt vom Unternehmen angegeben. Er kann deutlich über bzw. unter diesem Wert liegen.