Biologics Process Research & Development , Senior Scientist

Merck Merck · Pharma · NJ

This role at Merck focuses on Biologics Process Research & Development (BPR&D), aiming to efficiently develop innovative and robust manufacturing processes for biotherapeutics. Responsibilities include developing disruptive technologies, applying scientific principles to solve process development challenges, designing and conducting lab/pilot-scale studies, and collaborating with cross-functional teams. The role requires a Bachelor's, Master's, or PhD in a relevant scientific or engineering field with several years of experience, and proficiency in experimental design, data analysis, and problem-solving. Experience in upstream or downstream bioprocessing is essential. While AI/ML is mentioned as a preferred skill, the core of the role is in bioprocess development, not AI/ML model building.

What you'd actually do

  1. Develop innovative and disruptive technologies for next-generation biologic manufacturing processes
  2. Apply rigorous scientific principles and data analyses to solve challenging problems related to developing robust, cost-effective processes
  3. Develop and characterize robust processes for delivering multi-kilogram quantities of life-changing medicines
  4. Design and conduct lab and/or pilot-scale studies to support mechanistic understanding, scale-up, and transfer of processes to manufacturing
  5. Work with a collaborative, cross-functional team of talented scientists and engineers to advance the biologics pipeline from early- to late-stage development

Skills

Required

  • Bachelor's Degree with 4 years, or Master's Degree with 3 years or PhD with 0+ years of relevant experience
  • Chemical Engineering, Biochemical Engineering, Biomedical Engineering, Biotechnology, Biochemistry, Biology, Microbiology, or related fields
  • design and execute hands-on lab and/or _in silico_ experiments
  • Proficiency with statistical design and analysis tools
  • Excellent communication skills, ability to work in matrixed teams and collaborate with partners cross-functionally
  • demonstrated ability to think critically with excellent problem solving and troubleshooting skills
  • Knowledge of recombinant protein expression, metabolic pathways, biochemistry, and cell culture
  • Understanding of basic bioreactor principles, mass transfer kinetics
  • Understanding of cell & molecular biology
  • Sound scientific knowledge of protein properties and purification
  • Understanding of unit operations such as chromatography, filtration, crystallization, precipitation, adsorption, mixing etc.

Nice to have

  • History of external presentations and/or publications in peer-reviewed journals
  • Data science, modeling, machine learning, and artificial intelligence; proficiency with programming languages
  • Evaluating and introducing novel technologies and analytical tools in process development and manufacturing
  • Knowledge of protein biochemistry, biophysics, conjugation techniques
  • Vector construction, Genetic Engineering, and Systems Biology
  • Knowledge of cell-line development for protein expression in mammalian systems and suspension cell culture
  • Hands-on experience with RNA and whole-genome (re)sequencing, and bioinformatics analysis
  • High throughput experimentation using automation platforms
  • Familiarity with feed and media development for large-scale recombinant protein expression in mammalian systems
  • Knowledge of Quality by Design, Process Characterization and Control Strategy development
  • Biomanufacturing
  • Biomedical Engineering
  • Bioprocessing
  • Chemical Engineering
  • Data Analysis
  • Drug Delivery Technology
  • Flow Cytometry
  • High-Throughput Screening
  • Interpersonal Relationships
  • Microbiology
  • Molecular Biology Techniques
  • Molecular Microbiology
  • Multi-Color Flow Cytometry
  • Preformulation
  • Process Optimization
  • Production Process Development
  • Protein Biochemistry
  • Protein Expression
  • Protein Purifications

What the JD emphasized

  • hands-on lab and/or _in silico_ experiments
  • statistical design and analysis tools
  • data science, modeling, machine learning, and artificial intelligence; proficiency with programming languages