Associate Principal Scientist, QSP

TN United Kingdom
10 months ago
Applications closed

Related Jobs

View all jobs

Real World Data Scientist (Associate Director)

Principal Data Engineer

Associate Professor: Medical AI & Data Science Innovation

Associate Data Scientist - Meteorology/Oceanography (On-Site)

Associate Data Scientist

Associate Director Data Engineer

Social network you want to login/join with:

Associate Principal Scientist, QSP

Client:Certara

Location:United Kingdom

Job Category:Other

EU work permit required:Yes

Job Reference:0143c01cec68

Job Views:7

Posted:13.02.2025

Expiry Date:30.03.2025

Job Description:

Overview

About Certara

Certara is a growing company that provides a dynamic and exciting place to work. Our purpose is to assist in accelerating the development of meaningful medicines that make an impact on our society and the people that need them most. Innovation and creativity are highly valued, and everyone is given the opportunity for training and continuous development. Our portfolio spans the discovery, preclinical, clinical and post-marketing phases of drug development, working with 1,200 commercial companies, 250 academic institutions, and numerous regulatory agencies.

The Certara Quantitative Systems Pharmacology (QSP) group is a global organization focused on the impactful application of QSP and mechanistic PKPD modeling and simulation in drug discovery and development. We are leading several first-of-its-kind QSP Consortia with more than 10 global pharmaceutical companies and have a rapidly expanding consultancy portfolio. Our QSP scientists work in close collaboration with other Certara staff and clients to generate and use state-of-the-art mechanistic models for decision making in pharmaceutical R&D. The models are designed in close dialogue with clients and developed with a view to creating user-friendly tools that will inform drug development programs from discovery to regulatory filing. We have unique capability to seamlessly integrate bespoke QSP models into the Simcyp physiologically based pharmacokinetic (PBPK) platform. Besides our well-established leadership in applied QSP approaches in Immunology and Immuno-Oncology, we are now also the leading provider of QSP approaches in neuro-degenerative diseases through Certara’s recent acquisition of the In Silico Biosciences modelling platform.

We are seeking highly motivated and talented QSP modelling experts at all levels, who share our passion for using quantitative approaches to understand and impact complex drug discovery and development questions. Positions are available at various levels of experience across our global locations and for flexible, home-based roles.

Responsibilities

Technical

  1. Postdoctoral experience in systems modelling for drug discovery/ development teams.
  2. PhD (or equivalent) in life sciences, engineering, computer sciences, mathematics, physics or equivalent.
  3. Good understanding of PKPD, pharmacology and biology and its application in drug discovery and development.
  4. Very familiar and outstanding hands-on expertise with Matlab, Neuron or other similar modelling software.
  5. Strong publication record (commensurate with level of experience).

Team working

  1. Excellent interpersonal skills.
  2. Skilled and experienced at facilitating a multi-disciplinary team to work together on a complex project.
  3. Ability to communicate with all stakeholders clearly and efficiently.
  4. Organised and with track record of delivering quality results on time.

Personal

  1. Ability to work virtually with project teams across different locations and time zones.
  2. Leads by example.
  3. Self-reliant.

Other skills

  1. Highly computer literate and familiar with modern IT and communications technology.
  2. Good presentation skills.
  3. Combines scientific excellence with ability to make impact in drug discovery and development programs.
  4. Ability to manage multiple client project timelines and deliverables simultaneously.

Role (depending on experience)

  1. Overall responsibility for project delivery of quality QSP solutions on time.
  2. Provide hands-on technical support for model building when required.
  3. Work with clients to ensure they receive the expected added value.
  4. Work with the consortium/ consulting teams to ensure optimal deployment of resources.
  5. Work with Certara QSP line management to deliver optimum solutions.
  6. Provide general expert technical input across Certara QSP portfolio.
  7. Mentor other Certara QSP staff.

Qualifications

  1. Postdoctoral experience in systems modelling for drug discovery/ development teams.
  2. PhD (or equivalent) in life sciences, engineering, computer sciences, mathematics, physics or equivalent.
  3. Good understanding of PKPD, pharmacology and biology and its application in drug discovery and development.
  4. Very familiar and outstanding hands-on expertise with Matlab, Neuron or other similar modelling software.
  5. Strong publication record (commensurate with level of experience).

Certara bases all employment-related decision on merit, taking into consideration qualifications, skills, achievement, and performance. We treat all applicants and employees without regard to personal characteristics such as race, color, ethnicity, religion, sex, sexual orientation, age, nationality, marital status, pregnancy, physical or mental condition, genetic information, military service, or other characteristic protected by law.

#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

Neurodiversity in Machine Learning Careers: Turning Different Thinking into a Superpower

Machine learning is about more than just models & metrics. It’s about spotting patterns others miss, asking better questions, challenging assumptions & building systems that work reliably in the real world. That makes it a natural home for many neurodivergent people. If you live with ADHD, autism or dyslexia, you may have been told your brain is “too distracted”, “too literal” or “too disorganised” for a technical career. In reality, many of the traits that can make school or traditional offices hard are exactly the traits that make for excellent ML engineers, applied scientists & MLOps specialists. This guide is written for neurodivergent ML job seekers in the UK. We’ll explore: What neurodiversity means in a machine learning context How ADHD, autism & dyslexia strengths map to ML roles Practical workplace adjustments you can ask for under UK law How to talk about neurodivergence in applications & interviews By the end, you’ll have a clearer sense of where you might thrive in ML – & how to turn “different thinking” into a genuine career advantage.

Machine Learning Hiring Trends 2026: What to Watch Out For (For Job Seekers & Recruiters)

As we move into 2026, the machine learning jobs market in the UK is going through another big shift. Foundation models and generative AI are everywhere, companies are under pressure to show real ROI from AI, and cloud costs are being scrutinised like never before. Some organisations are slowing hiring or merging teams. Others are doubling down on machine learning, MLOps and AI platform engineering to stay competitive. The end result? Fewer fluffy “AI” roles, more focused machine learning roles with clear ownership and expectations. Whether you are a machine learning job seeker planning your next move, or a recruiter trying to build ML teams, understanding the key machine learning hiring trends for 2026 will help you stay ahead.