Abzu is breaking new ground in the life science and pharmaceutical industries in early research, clinical development, and digital health. We are looking for a curious and experienced bioinformatician who is interested in solving real-world problems in an entirely new way with our proprietary technology.
You will be an integral part of a multi-disciplinary environment in Barcelona who works in close collaboration with the rest of the Abzu team in Copenhagen. You will play a leading role in bringing the latest advancements in our core technology to the life science and pharmaceutical industries.
Specifically, you will be part of our forward-looking team composed of bioinformaticians, computational chemists, data scientists, and project managers, and collaborate with industry experts in various fields. With your analytical skills and experience in the life sciences, you’ll help ensure that our customers reveal new insights and identify non-trivial relationships with our explainable AI.
Ideally, your approach to solve some of the most challenging problems and experiences from the industry will enable us to demonstrate the unique value of our pioneering technology. Your role will require you to work on complex, varied, and often small datasets. In this role, you will introduce recommendations to our customers that may require them to change their operations or processes, so it is essential that you are able to translate the value we bring.
This role is ideal for someone with an interest in machine learning, a passion for bringing the latest research to real applications, and a strong desire to take responsibility for improving our technology and product even further.
We’re an open-minded bunch of nice nerds, and even if you do not meet all of the criteria listed below but are excited about the opportunity, please don’t hesitate to apply or ask questions. We are here to grow together and bring Abzu one step closer to realizing the promise of explainable artificial intelligence.
- You have a PhD in a relevant field in the life sciences (systems biology, pharmacogenomics, genetics, computational biology, etc.)
- You bring +3 years of experience working with complex data problems in the biotech or pharmaceutical industries, specifically in drug development
- You can show proven application of advanced analytical, data science, and statistical methods in the commercial world
- You have customer-facing skills, are curious about customer problems, and want to use our technology to cut through the noise of biological data
- You are entrepreneurial in spirit and like to explore external opportunities (academic collaborations, industry partnerships, etc.)
- You have experience with data science in Python (sklearn, statsmodels, pandas, numpy) or R
- You have good presentation and communication skills with a knack for explaining complex analytical concepts to people from other fields
- You’re willing to travel approximately every month / 2 months to Copenhagen (or elsewhere for Abzu gatherings, client meetings, industry conferences, etc.)
We’d love it if...
- You are a fast learner and a good teacher
- You have a passion for AI, machine-learning, and research
- You’re a curious and ambitious good human
- You like public speaking and presenting :)
Founded in February 2018, Abzu is an applied research startup with offices in Copenhagen, Denmark and Barcelona, Spain.
Abzu was born from the desire to challenge the fundamental assumptions of contemporary, black box AI. Abzu’s pioneering artificial intelligence, the QLattice®, accelerates analysis and insights through transparent and explainable models.
You’ll have the opportunity to be part of a highly-skilled, fast-thinking, and energetic team. Our philosophy and culture are based on self management, which empowers people to be themselves and make their own decisions about their work.
We are focused on creating the best environment where people have integrity, a strong sense of responsibility, and collaborate in creative and inspiring ways. We believe and trust in people, their high potential, and inestimable value.
This requires transparency and trust, which is an integral part of our technology and who we are. This organizational style is not a fit for everyone.
Our mission is to build a machine where cognition arises through self-organization of millions of interactions. We are bringing explainable artificial intelligence to researchers and scientists worldwide.
With the rapid advancement of machine learning, anyone can fit a model to a dataset. However, it is still too complicated to explain what is going into a decision, why a specific outcome happens, and what's truly important.
Our graph-based technology is currently used in the life science and pharmaceutical industries to find answers to problems by leveraging our technology’s "explorative" ability to test millions of potential models and seamlessly pick the simplest and most accurate ones.
As a result, researchers and scientists can test hypotheses faster than ever using one standardized machine learning framework to interpret and explain what is going into a decision (and not just predicting it).
We look forward to hearing from you!