Postdoctoral Scholar in Silico Formulation Design
il y a 3 jours
**Function**
- Career Programs
**Sub function**
- Post Doc - R&D Product Development
**Category**
- Post Doc - R&D Product Development (ST5)
**Location**
- Beerse / Belgium
**Date posted**
- Jun 26 2025
**Requisition number**
- R-019457
**Work pattern**
- Hybrid Work
Description
**Job Function**:
Career Programs
** Job Sub Function**:
Post Doc - R&D Product Development
** Job Category**:
Career Program
** All Job Posting Locations**:
Beerse, Antwerp, Belgium
** Job Description**:
**About Innovative Medicine**
Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.
Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.
Pharmaceutical & Material Sciences is, within the Pharmaceutical Development & Supply (PPDS) organization of the Pharmaceutical Companies of Johnson and Johnson, responsible for high-throughput experimentation, preformulation, biopharmaceutics, solid state form selection and understanding, and material selection and qualification.
Johnson & Johnson is currently seeking a **Postdoctoral Scholar In Silico Formulation Design**to be located in Beerse, Belgium. This position is fixed-term contract of 2 years.
Within this role you will provide expert scientific advice to drive computational approaches and in silico predictions in support of formulation design of solid and liquid dosage forms.
The **overall mission** of the position is to work together with a team of experts in molecular design, solid form design and formulation design and provide in silico support to select, develop and understand the behavior of Active Pharmaceutical Ingredients, functional excipients, and drug formulations in each phase of development.
Principal Responsibilities:
- Conduct computational studies to investigate the behavior and interactions of the active pharmaceutical ingredients and functional excipients in drug products and physiological environments.
- Develop, optimize, and validate machine learning models to predict the properties and performance of formulations.
- Analyze complex data sets to identify patterns and insights that inform formulation design.
- Review and expansion of the internally available catalogue of computational tools.
- Drive innovation in computational flows and approaches to support drug delivery of synthetic molecules.
- Liaise with experimental analytical and formulation scientists to contextualize the relevance of modeling in product development.
- Take part in research collaborations with academic and private organizations and consortia.
- Work in a multidisciplinary team of researchers, internally as well as externally building and maintaining a strong relationship with key stakeholders.
Education and Experience Requirements:
- Ph.D. in Computer Science, Data Science, Pharmaceutical Sciences, Chemical Engineering or a related field with experience in AI/ML and simulation technologies.
- Proficiency in programming languages such as Python or R.
- Experience with machine learning frameworks (e.g., TensorFlow, PyTorch).
- Familiarity with statistical analysis and data visualization tools.
- Insights into the broader pharmaceutical product development picture and formulation design is considered an advantage.
- Team player, dynamic, creative, innovative and flexible.
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