Senior Human Genomics Scientist

Rare genetic diseases affect 400 million people worldwide. A diagnosis takes five years due to genetic testing challenges. In the near future, understanding the results of sequencing the patient's genome will be the main challenge. The current manual process requires a high level of expertise and a lot of time to determine which of thousands of genetic aspects of a patient are responsible for the disease. Genetic disease patients needing a diagnosis don't have that time. How can we streamline this process? At Nostos Genomics, we believe technology like machine learning and simplicity are key.

We are a venture-backed healthtech start-up supported by leading investors and scientists on a mission to improve the lives of 400 million people around the world who suffer from rare diseases. The platform we have developed uses artificial intelligence and computational biology to decipher how changes in our DNA can lead to disease. Through this platform, we enable genetic testing labs to provide clear and fast diagnoses to more patients.

For this, we've gathered one of the best teams of experts in genomics, machine learning, and business development. Our people aren't just part of a team, they're part of something bigger. Together, we share the mission of building AION, our platform part of a new generation of precision medicine that allows rare disease patients to make informed decisions about their health. 

Your role

We are looking for a Senior Human Genomics Scientist to work closely together with our computational genomics, engineering and product team to shape the scientific direction of our software. You will be responsible for the development and implementation of bioinformatics approaches to improve the clinical interpretation of genetic data through our platform. You will be a key contributor to our scientific pipeline, ensuring it remains at the forefront of clinical genetics. You will be expected to:

• Harness your deep expertise in human genomics and rare diseases to co-create, refine, and validate genetic diagnostic algorithms, methodologies, and pipelines.

• Dive into genetic data, including VCF files and clinical data, extracting meaningful insights to enhance our variant interpretation methods.

• Bring your coding skills to the table, ideally with experience in developing and maintaining production-level code for genomic data analysis.

• Collaborate effectively with cross-functional teams, including computational genomics, engineering and product to ensure seamless integration of scientific advancements into our software platform. Your ability to convey complex scientific concepts to non-technical colleagues is key.

• Champion the development and implementation of quality control processes to ensure accuracy, reliability and reproducibility in our genetic diagnostics.

• Collaborate with our regulatory affairs team to ensure compliance with essential regulations, such as IVDR, as we strive for the highest industry standards.

• Stay at the forefront of genomics science and technology through ongoing learning and skill development. Contribute to research and development efforts aimed at enhancing variant interpretation accuracy and efficiency.

Requirements

Who we are looking for:

• Post-doctorate or equivalent work experience in human genetics, human genomics, computational genomics, bioinformatics, molecular biology or a related discipline.

• Experience analysing human exome, genome or transcriptome datasets, especially linking molecular alterations to clinical phenotypes. 

• Proven track record of developing custom algorithms for the analysis of genetic data, particularly from NGS.

• Solid working knowledge of the latest tools, software and reference databases for clinical NGS analysis. Familiarity with genetic variant interpretation, ACMG guidelines and/or variant effect prediction algorithms.

• Intermediate to advanced coding skills in Python, with experience in production-level code development.

• Familiarity with agile software development methodologies and project management practices.

What will make you stand out

• Prior experience in a start-up environment.

• Track record of scientific contributions to