Bioinformatics Engineer

cfdx is building the worlds first AI precision neuroscience company. We are at the start of our journey first tackling the hardest problem in the space: understanding the basis of neurodegeneration. We will be developing novel diagnostics and target discovery platforms to impact the lives of hundreds of millions globally.

Now venturebacked with leading funds in Europe and the US we are building the founding team. We are valuedriven and committed to curating an environment that will foster the worlds best AI and neuroscience research team.

Responsibilities:

As an earlystage startup you will be taking ownership of drylab operations including:

NGS bioinformatics pipeline development (scaling up to 1000s of samples)

cloud infrastructure and core software engineering

QC and data analysis

Research and marker discovery related to neurological diseases

Feature engineering for machine learning pipelines

Providing domain knowledge for multiomic large biological foundation models (LLMs)

Requirements:

Required:

Hold a PhD or equivalent industry experience in computer science bioinformatics computational biology or a related field

Firsthand experience with endtoend bioinformatics tools used to process sequencing data from raw reads all the way to analytical outputs

Operational software engineering skills: the ability to write highquality code to be the backbone of our SW stack

Proven trackrecord of analysing high throughput NGS and multiomics data in realworld context

Good working knowledge of workflow managers including but not limited to NextFlow.

Good working knowledge with cloud computing environments including but not limited to AWS.

Desirable:

2 years of industry experience in building operating and scaling biological data pipelines

Domain knowledge with advance artificial intelligence approaches and experience applying them to a biological context

Familiar with data wrangling analysis and visualisation libraries using Python (preferable) R or Julia

Expertise with statistical approaches applied to evaluating biological datasets.

Please use the below link for job application and quicker response.

Remote Work :

No