Head of Quantitative Biomarker Sciences (all genders) at Evotec

Hamburg, , Germany -

Full Time

Start Date

Immediate

Expiry Date

19 May, 26

Salary

0.0

Posted On

18 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Biomarker Data Modelling, QSP Models, AI/ML, Image Analytics, Multi-omics Data Integration, Pharmacometrics, Clinical Development, Biostatistics, Pathology, Statistical Modelling, Machine Learning, R, Python, Team Leadership, Study Design, Data QC

Industry

Biotechnology Research

Description

The global Translational Biomarker department at Evotec supports the discovery and validation of markers, enabling better translatability of Evotec's and client's drug discovery and development projects. We are now searching for a Head of Quantitative Biomarker Sciences (all genders) Full time and permanent who will lead a multidisciplinary team responsible for transforming discovery and (pre)clinical biomarker data into decision-driving evidence. This leader oversees biomarker data modelling across scales (small scale to big data), establishes and applies QSP models in partnership with Pharmacometrics across sites, develops AI/ML approaches for tissue image analytics (IHC/ISH), and delivers integrated analytics of Olink/NULISA panels and multi-omics data paired with clinical outcomes. The role is highly collaborative, working closely with AI/ML, in silico, pathology, pharmacometrics, clinical development, and biostatistics to accelerate therapeutic decision-making and biomarker strategy. The focus is exclusively on clinical and molecular biomarker data and its translation to program strategy and evidence packages. Key Responsibilities Define and execute the Quantitative Biomarker Sciences (QBS) strategy across our programs – from late-stage discovery to early-stage clinical trials. Build, lead and develop a high-performing team of scientists and technical specialists; set goals, mentor talent, and cultivate a culture of open communication, scientific excellence and trust Establish standards, governance, and best practices for biomarker data modelling, code quality, documentation, and model lifecycle management. Proactively lead the development of statistical and machine learning models for discovery and preclinical biomarker datasets (e.g., longitudinal, high-dimensional, multimodal). Co‑lead QSP model development with Pharmacometrics; align model assumptions, parameterization, and validation with clinical and translational biology. Develop and evaluate AI/ML pipelines for IHC/ISH image analytics (e.g., segmentation, cell phenotyping, spatial features) and integrate them into biomarker projects, including validation against pathology truth sets and clinical endpoints. Oversee integrative analyses connecting platforms, such as Olink/NULISA, and multiple biomarkers with clinical outcomes, safety signals, PK/PD, and exposure–response. Serve as the principal QBS counterpart to Pharmacometrics, Clinical Development, Biostatistics, Pathology, AI/ML, and in silico modelling teams. Provide clear, decision‑oriented communications and visualizations to study teams, governance, and external partners in a timely manner. Contribute to study design, sample strategy, and endpoint selection, including assay readiness and analytical performance considerations. Lead and/or represent biomarkers, biomarker projects (stand-alone) and QBS in external collaborations (CROs, academic partners, consortia) and within project teams Qualification PhD (or equivalent experience) in Computational Biology, Bioinformatics, Biostatistics, Applied Math, Systems Pharmacology, or related field Extensive experience in quantitative (biomarker) analytics, data science, pharmacometrics/systems modeling, or related domains, combined with proven leadership of diverse teams of scientists and/or specialists Demonstrated experience with biomarker modeling (e.g., modelling of multiplex data, Olink, histopathology image analysis, multi-omics integration, clinical metadata integration) with downstream influence on study or portfolio decisions. Deep Know-how and proven experience with AI/ML tools and implementation Preferably hands‑on or oversight experience in QSP modelling (e.g., mechanistic, hybrid, or empirical) Expertise in statistical modelling and ML for high‑dimensional data (e.g., mixed models, survival analyses, regularized models, tree-based and deep learning methods). Demonstrated experience with scripting/coding languages, such as R and Python Understanding of assay characteristics (e.g., LoD, precision, batch effects), data QC, and integration with PK/PD and clinical endpoints. Proven ability to lead cross‑functional science, set clear priorities, and deliver to milestones. Exceptional communication skills Our offer: A position within a vigorous and exciting professional environment promoted by an open culture and a spirit of community A diverse, international workforce with a dynamic working environment that fosters creativity, innovations and teamwork 30 days of annual holiday, monthly allowance for public transportation, and in-house canteen Capital forming benefits, flexible working hours, holiday pay, and annual bonus depending on performance To apply, please click on the “Apply” button and provide your application documents (CV and cover letter, including earliest possible start date and salary requirements). We are looking forward to getting to know you and to your application. FR : Dans le cadre de sa politique Diversité, Evotec étudie, à compétences égales, toutes les candidatures dont celles des personnes en situation de handicap. ENG : In the frame of our Diversity policy, Evotec considers, with equal competences, all applications including people with disabilities. Evotec is a life science company with a unique business model that delivers on its mission to discover and develop highly effective therapeutics and make them available to the patients. The Company’s multimodality platform comprises a unique combination of innovative technologies, data and science for the discovery, development, and production of first-in-class and best-in-class pharmaceutical products. Evotec leverages this “Data-driven R&D Autobahn to Cures” for proprietary projects and within a network of partners including all Top 20 Pharma and over 800 biotechnology companies, academic institutions, as well as other healthcare stakeholders. Evotec has strategic activities in a broad range of currently underserved therapeutic areas, including e.g. neurology, oncology, as well as metabolic and infectious diseases. Within these areas of expertise, Evotec aims to create the world-leading co-owned pipeline for innovative therapeutics and has to-date established a portfolio of more than 200 proprietary and co-owned R&D projects from early discovery to clinical development. Evotec operates globally with more than 5,000 highly qualified people. The Company’s 17 sites offer highly synergistic technologies and services and operate as complementary clusters of excellence. For additional information please go to www.evotec.com and follow us on X/Twitter @Evotec and LinkedIn. Please click on the link below to access and review our Privacy Information for Applicants: Privacy Information for Applicants

Responsibilities

This leader will define and execute the Quantitative Biomarker Sciences strategy across programs, leading a multidisciplinary team responsible for transforming biomarker data into decision-driving evidence. Key tasks include overseeing biomarker data modeling, developing AI/ML approaches for image analytics, and delivering integrated analyses of multi-omics data paired with clinical outcomes.