Senior Bioinformatician - Tertiary Analysis

We believe that there is a smarter, more data-driven way to make decisions in healthcare. combines genomics, radiomics, clinical, and other data modalities through our propriety SOPHiA DDM platform to help healthcare professionals and patients across the world in the fight against cancer and rare and inherited diseases. To help us achieve our ambitious mission, we are now searching for a Senior Bioinformatician to join our Tertiary Analysis team in our Bidart, France or Rolle, Switzerland office.

Your Mission:

As a Senior Bioinformatician on our Tertiary Analysis team, you will focus on the annotation and the interpretation of genetic variants (and other clinically relevant features) present in genomic data. The Tertiary Analysis team identifies, handles, and validates the contextual information supporting the genomic experts in their interpretation of results. This includes:

1. The design, evaluation and integration of predictive models and algorithms to prioritize variants and their effects;
2. The integration of expert knowledge from multiple data resources and repositories.

The value add:

• Conceive and research models and algorithms for variant effect prediction and variant prioritization, on either somatic or germline contexts.
• Apply subject matter knowledge in cancer and/or Mendelian genomics to guide the design of solutions for variant interpretation and collaborate on the implementation with a team of developers.
• Design and carry-out reproducible analytical performance benchmarks of statistical models and algorithms.
• Communicate and discuss designs and developments with management, the team and project managers.
• Lead the preparation of technical materials such as white papers for tertiary analysis workflows.
• Provide topic knowledge support to other teams at multiple stages of product development.
• Regularly engage with scientific literature in the field of cancer and/or medical genomics as well as with clinical guidelines and standards for variant interpretation.
• Collect and curate ground-truth datasets for algorithm performance benchmarking.

• PhD in cancer genomics, medical genomics, computational biology, functional genomics, population genetics, or similar field. Strong publication record in the field of expertise is required.
• At least 5 years of experience in computational biology. Ability to understand the inner workings of state-of-the-art algorithms related to variant prioritization and variant effect prediction.
• Working knowledge of cancer genomics and/or medical genomics is a must. Demonstrated experience in a clinical genetics or genetic diagnostic setting is highly desirable.
• Excellent communication skills, including experience in communicating complex scientific principles in simple terms to varied audiences.
• Competence in programming languages common in the bioinformatics field (e.g. Python, R), demonstrated experience in reproducible research (routine use of code versioning, environment configuration tools and scientific workflows).
• SQL and bash scripting experience is an advantage.
• English is required.

You will be joining an organization with the patient at the heart of every decision and action, driven by purpose as we drive exponential growth. 

• Opportunity to work on cutting-edge research projects with an immediate global impact. 
• A flexible, friendly and international working environment with a collaborative atmosphere 

• An exciting company mission that brings together science and technology to directly impact the lives of patients with life threatening illness. 

• A fast-growing company with plenty of opportunity for personal growth and development 

• A hard technical challenge to solve with exciting modern technology - cloud computing, Big Data, DevOps, machine learning 

The Process 

Apply now with your CV and any supporting information. All resumes MUST be in English for a successful review. 

Start Date: ASAP 

Location: Bidart, France OR Rolle, Switzerland (3 days in office)

Contract: Full-Time, Permanent