T2604 Research Fellow AI-Enhanced Pharmacometrics (Intern)

AtDebiopharm every step we take is guided by one purpose: improving the lives of people affected by cancer and infectious diseases. As a privately-owned Swiss biopharmaceutical companyweredriven by science butabove all bythe people behind every treatment the patients and their families.

Through our unique development only model we bring forward promising therapies and transform them into treatments that can reach those who need them most faster.

Are you ready to be at the forefront ofthemodel-informed drug development (MIDD)DebiopharmInternational SAisseekinga highly motivatedResearch Fellow (Intern)to help build an AI-enhanced Quantitative Systems Pharmacology (QSP) platform. This project offers a unique opportunity to integrate preclinicalclinical dataand real-world datawithmathematical models andAI to accelerate the development of our Antibody-Drug Conjugate (ADC) pipeline. You will work directly on assets bridging the gap between systems biology and data-driven decision-making.

Research Fellow AI-EnhancedPharmacometrics(Intern)

Location:Lausanne Switzerland

Department:Clinical Pharmacology & Pharmacometrics

Project:12-months internship

Executive Summary of the Internship

The primary mission of this fellowship is to develop and standardize a custom QSP platform for theDebiopharmADC pipeline. ByutilizingAI and advancedmodelingtechniques you willcontribute toa Digital Twin environment to simulate virtual trials optimize dosing regimens andestablishGo/No-Go criteria. This role is central toa specific projectstrategy aiming to shorten development timelines and enhance our proprietaryMIDDcapabilities.

Key Responsibilities

• QSPData Integration:Contribute to integrating multidatasource into theexistingQSP platform for key ADC programs.

• AI-Driven Modelling:Create templates for virtual population construction using AI and R to characterize populations of interest.

• SimulatorDevelopment:Build virtual trial simulators using R or Cfor predictingcompound efficacy and safety.

• Decision Analysis:Develop R-based data analysis templates to define Go/No-Go criteria based on virtual trial simulations.

• Documentation:Thoroughly document the development process andanalysisworkflows to ensure knowledge retention.

Profile Required

• Educational Background:PhD orMastersstudent in Pharmacometrics Biostatistics Computational Biology Mathematics Computer Science or Engineering.

• Core Knowledge:Understandingbasic Pharmacokinetic (PK) and Pharmacodynamic (PD) concepts.

• ModelingSoftware:Strongproficiencyin R or Python is to Monolix NONMEMMatlaborSimBiologyis a significant C is considered a strong plus for simulator development.

• Team Synergy:Ability to work independently on technical tasks while collaborating effectively in a team environment.

• Organization:Strong organizational skills to manage and process data from multiple ADC programs simultaneously.

• Communication:Fluency in English (both oral and written).

WhatweOffer:

• Being part of a company where innovation collaboration and impactarentjust values theyrehow we work every day

• Partner with teams across disciplines at the forefront of oncology and anti-infective development

• An inclusive and respectful workplace proud to be Equal-Pay certified

• Grow in a culture that values people purpose and performance

• A chance to grow share and shape the future of healthcare

What to Expect in the Recruitment Process:

If your application is selectedyoullbe invited to interviews with Talent Acquisition and the Hiring Manager via Teams followed by apanelinterview and reference checks. Communication is handled via Workablecheck your spam folder for emails from*@.

Please contact our HR Department prior tosubmittingany profiles. We cannot accept unsolicited applications from agencies or recruiters.

Required Experience:

Intern