Research Scientist - Computational Biology
Systematic Medicine aims to extend human health span by targeting the root causes of ageing. In particular we focus on genomic damage that accumulates over a lifetime and contributes to age-related disease burden. We are hiring a Computational Research Scientist to help shape our experimental research.
About the role
Our team is focused on the high-accuracy detection and targeting of mutated cells, an approach particularly suited to the selective killing of cancer.
You will work in a small, multidisciplinary team of research scientists, including laboratory biologists and computational scientists. You will use a broad range of quantitative approaches to
Model and design experiments in close collaboration with the lab team.
Analyse results from experiments.
Guide future experiments.
The logical structure and organisation of the genetic code provides particularly valuable opportunities for quantitative reasoning.
Ageing is an extremely challenging problem. Treating cancer is one step along the way.
About you
A strong foundation in a quantitative field
A degree in statistics, mathematics, computer science, physics, biophysics, or a related discipline.
A postgraduate degree is preferred but not required.
Research experience
Two or more years in a scientific or R&D; context.
Meaningful work experience outside academia
Some exposure to a non-academic context.
Biological knowledge, or the interest and ability to learn it quickly
Molecular biology and genomics,



with some general physiology or systems knowledge.
Candidates with strong quantitative backgrounds but without initial biology knowledge will still be considered. We have seen successful candidates learn the relevant biology on the job.
Skills
Robust scientific programming skills (Python preferred) and the ability to develop code collaboratively within a team.
Strong statistical reasoning and understanding of hypothesis testing.
Strong scientific reasoning and understanding of experimental design.
The ability to communicate and document quantitative thought process in an clear, logical and organized manner.
The ability to adapt methods to the problem at hand. We are not committed to particular techniques and prefer candidates who can select and learn appropriate approaches rather than relying on a single specialization.
The ability to reason about and design code for novel research problems that are not suited to off-the-shelf tools and bioinformatics packages.
Comfort working on data-poor problems that are not suited to machine learning approaches.
About us
We work on meaningful, challenging problems and approach them with a rigorous scientific mindset.
We have secure, long-term private funding (no need to write grants).
We are based in the Jumar incubator in the CSL Building in Parkville, Melbourne, with access to excellent facilities.
We value dedicated, focused work but do not require long hours.
#J-*****-Ljbffr

📌 Research Scientist - Computational Biology (Melbourne)
🏢 Systematic Medicine
📍 Melbourne