Senior Med Chemist
We are looking for a leader to establish the drug discovery and development team and rapidly progress our drug discovery programs through small molecule hit to lead optimisation.
You will work with the AI and Biology teams to deliver our drug discovery pipeline and work with the cheminformatics and machine learning teams to enhance the technology platform.
We are Ladder Tx, a digitally native company operating at the intersection of novel chemistry, machine learning and RNA biology to shine light on the dark genome. We are creating an in-silico and in-vitro platform that enables the discovery of small molecule modulators of RNA.
The current toolkit for developing drugs is focused almost entirely on protein targets. The actions of these proteins, however, are known to be influenced by areas of the genome that do not encode proteins, the non-coding genome, which encodes RNA. Variation in the non-coding genome, the “dark genome” is associated with many diseases but remains inaccessible by classical drug discovery. Our mission is to change this, by engineering molecules capable of targeting the dark genome.
We are curious, nimble, breaking new ground and growing fast. Come make an impact with us and be part of our story.
In this role, you will establish the team and process to design RNA targeting small molecules to impact patient lives.
Collaborating with the cheminformatics and machine learning teams to build a chemistry and in silico design strategy
Ensuring hit identification, hit to lead and lead optimisation for Ladder Tx drug discovery programs
Collaborating with cheminformatics team members to identify novel compounds based on biological, ADME and ML predictions to drive lead identification and lead optimisation.
Developing relationships with key CROs or collaborators to coordinate compound synthesis, characterisation and submission in alignment with company goals and timelines.
Building and maintaining productive relationships with the cheminformatics and machine learning teams to drive the continuous development of computational tools that accelerate the Ladder Tx pipeline
Curious, scientifically minded and rigorous. Good communicator, team-player and significant attention to detail.
PhD in medicinal chemistry, computational chemistry, cheminformatics or related fields.
5+ years of experience in a drug discovery environment with a demonstrable track record of optimising small molecules to drug candidates, across different target classes.
An interest in leveraging machine learning to accelerate drug discovery
Domain knowledge in traditional organic chemistry, medicinal chemistry principles and modern approaches to compound design.
Highly motivated with a track record of success.
Nice to haves
Domain knowledge in medicinal computational chemistry and or ligand/structure-based drug design
Experience designing molecules that target RNA
What we offer
The opportunity to accelerate your career. You will have significant authority and responsibility, with the opportunity to grow into leadership roles quickly.
The opportunity to make a difference. Your work will have a direct impact on the experiments we run, and will influence our programs destined for the clinic to affect patient outcomes.
A place to explore the range of your interests. We pride ourselves in an environment that cultivates curiosity, creativity and autonomy. At Ladder the “why” of things is always the most important question.
An environment designed to broaden your perspectives. We care deeply about inclusive working practices and diverse teams. Diversity is integral to our success, and an inclusive environment allows the team to do their best work.
A place to push your skills. We strongly encourage publication of our work and presentation of your work at industry leading conferences.
An expert team of advisors to help you develop. Our stellar scientific advisory board includes industry leaders in Pharma, AI, and RNA Biology. You will work closely with thought leaders in the field and shape the future of RNA drug discovery.
To apply send over a CV to firstname.lastname@example.org