DeepLab is a startup working on custom machine learning solutions for enterprises applying state-of-the-art AI and machine learning technologies. It consists of a group of visionary enthusiasts engineers holding a PhD in machine learning with more than 10 years research and working experience. Specifically we design and develop solutions employing machine learning in a broad spectrum of problems: computer vision, natural language processing, speech recognition, recommendation systems and more.
This call is addressed to candidates with a strong desire to work with new machine learning technologies, such as deep learning, and to be part of the emerging technological and scientific trends: employing huge amounts of data, conducting beyond-state-of-the-art research and development, employing methods and tools at the scientific and technological frontiers. Deeplab calls for outstanding candidates, experienced and/or highly enthusiastic, engineers or not, who would like to face challenging tasks, developing applied research and technology in an international environment, and in collaboration with big academic and industrial players.
Senior Bioinformatics Data Scientist
Job descriptionWe seek outstanding and experienced candidates who would like to face challenging tasks, developing applied research and technology in an international environment to build our deep-learning powered bioinformatics sub-group. We envision this group to conduct disruptive R&D in collaboration with big academic and/or industrial collaborators. We seek enthusiastic candidates for integrating, and analysing multi-omics biomedical data to develop biological insights and to design the respective end-to-end machine learning powered pipelines/models. Machine learning (ML)/deep-learning (DL) algorithms have recently revolutionized, beyond others, the pharma research and industry too, by advancing the analysis and modeling of biomedical data. Tasks of interest span a wide range of applications such as drug discovery, virtual screening, single-cell (epi)-genetic and multimodal single-cell omics data analysis and integration. Our goal is to collaborate with the experts and stakeholders worldwide and further leverage the advantages of DL to improve diagnostics, identify novel treatments, and offer clinical insights into both disease and wellness, contributing a substantial added value with health impact in the society.
- Managing, preprocessing/ processing, integrating and analysing large biomedical datasets for biological insights.
- Deep understanding of biomedical use cases/ problems and contributing in formulating solutions with machine learning pipelines. Designing and developing machine learning/ deep learning software pipelines/ systems that are built to consume and analyse biomedical data while dealing with clustering, classification and regression problems; Batch experimental benchmarking in large datasets.
- Managing a cross-functional team that brings together the best in class Informatics, AI, Engineering, Drug Discovery and Product capabilities to tackle the scientific challenges.
- A PhD in bioinformatics, computational biology or related field of research.
- Experience with proven track record on implementing machine learning systems in industrial or large scale applications; Solid background knowledge and deep understanding of biomedical areas. Deep understanding of ML algorithms, of DL fundamentals and up to date with recent DL advancements, especially related to the fields of interests.
- 3-5+ working experience on integrating and analysing large and/ or popular/ recent 'omics/biomedical datasets to directly support Drug Discovery activities; Hands-on experience in processing large scale genomic datasets, such as transcriptomic, proteonomic or epigeonomic data.
- Expertise/ experience in primary biological interpretation based on the integration of biomedical datasets to support applications in Drug Discovery and/or other omics fields.
- Strong programmic ability in language packages that support Bioinformatic, Data Science and Machine Learning code and pipelines such as Python, PyTorch, numpy, spicy, etc.
- Experience with databases and other technologies we like such as: Github and Jupyter. Good to have experience in: BigQuery, ElasticSearch, MySQL, MongoDB, Spark, Kubernetes, AWS/GCP.
- Leading and management skills, strong communication skills to communicate presentation of complex analyses in a clear, concise and actionable manner.
- Excellent written and oral communication skills and ability to build strong relationships in a challenging international environment.
- Supplementary private health insurance.
- Work with bright research ML engineers team members and collaborators around the world.
- Working in high-end AI- tech and having an impact in real- world applications.
- Fresh working environment at our new offices.
- Flexible working hours and work from home.
- Competitive salary depending on qualifications, expertise and experience.