Ardigen enables AI transformation for biotech and pharmaceutical companies to leverage the full potential of data. The company delivers value at the intersection of biology and computational methods to increase the likelihood of success and accelerate the drug discovery process. With our platforms based on advanced algorithms and state-of-the-art technology, we help researchers to get scientific insights from a large amount of data, leading to new discoveries and breakthroughs in fields such as personalized medicine and drug development.
Let's grow together & code against cancer!
- Application of computer vision methods to high-content screening data
- Application of language models and structural biology methods to analyze and optimize protein sequences of biologics (e.g. antibodies)
- Development of deep representations of multi-omics data to better understand selected diseases
- Application of AI in small molecule optimization and virtual screening
Application of NLP (and LLMs in particular) to develop AI assistants in the context of drug discovery
Taking on roles related to technical leadership within teams working on the development and application of the technologies mentioned above
Acting as a reliable discussion/collaboration partner for our commercial and academic partners
Designing and applying methods based on machine learning and deep learning to solve various problems in drug discovery
Implementing and deploying machine learning models using Python (with frameworks such as PyTorch, TensorFlow, scikit-learn, and others)
Staying up to date with current research and methodology on applying machine learning and deep learning to life sciences
Providing guidance to junior colleagues
MSc or PhD in computer science, mathematics, statistics, physics, cheminformatics, computational biology/chemistry, or a related field
At least 6 years of relevant work experience (in either commercial or academic setting)
Extensive hands-on experience in projects using methodology from various areas of data science: deep learning, machine learning, statistical learning, data mining, natural language processing, or big data solutions, as well as good understanding of the theory behind these methods
Extensive knowledge and intuition on statistical and machine learning methods and concepts (regression, classification, validation procedures, dimensionality reduction, clustering, feature selection, data mismatch, domain adaptation, etc.)
Strong programming skills in Python and good programming practices
Experience with deep learning frameworks (with a slight preference towards PyTorch)
Experience with distributed version control systems (Git or equivalent)
Eagerness to learn the domain context of the application of AI methods in Drug Discovery
Ability and willingness to pass knowledge to others and guide less experienced colleagues
Organizational and interpersonal skills
Excellent verbal and written communication skills, including the ability to summarize technically complex information for a non-technical audience
Proficiency in English (C1)
Flexible working hours
Employee Stock Option Plan
Mental health support (HearMe Platform)
English classes
Funding for professional development, training, and internal mentoring program
The opportunity to not just code, but to code with a purpose to make a difference - making a meaningful impact through your daily work #CodeAgainstCancer
Private medical care
Multisport card