Target Discovery Scientist

Role Overview

As a Target Discovery Scientist you will play a vital part in our target generation and biomarker discovery efforts. You will provide project teams with scientific analysis for the preclinical assessment of potential candidates generated from Nomaly, our differentiated platform technology. You will contribute to the assessment and prioritisation of novel drug targets primarily on an understanding of the molecular biology of the target, linking it via function to disease biology. In some cases potentially following up by profiling target safety and progressability.

Key Responsibilities

• Evaluating functional and molecular mechanisms for a genetic influence on a disease
• Find and analyse databases, resources and literature to build the case for your hypotheses
• Weigh multiple sources of evidence, triage and prioritise leads, and independently investigate and build a story around a biomedical hypothesis
• Depending on your experience, review and analyse a range of evidence such as tissue/cell expression data, independent genetic evidence, interaction data, protein structure and sequence analysis, clinical data, published disease model, animal or organoid results, ontologies, etc.

Qualifications

You will have a strong background in either biology or bioinformatics, most likely with a proven track record of publishing high-impact biological papers, and most of these:

• PhD in Genomics, Molecular or Cell biology, Bioinformatics, Computational Biology, or a related field
• Strong knowledge of molecular biology, an understanding of genetics, and ideally experience interpreting disease mechanisms
• Proven track record of publishing high-impact scientific papers in biology, or in delivering and completing projects or objectives using analytical and problem-solving skills
• An understanding of the statistics and the principles behind human genomics is preferred, and/or (optionally) experience in genomics research e.g. working UKBiobank, 1000 genomes, other genetic cohorts or any form of genetic data
• (optionally) Programming skills, particularly in languages such as Python or R
• A desire to learn and embrace new approaches
• Good communication and teamwork skills