Project Lead Artificial Intelligence & Data Science
Oude Campsweg 35C, 2678 NN De Lier, Netherlands
Dümmen Orange is the world’s largest breeder and propagator of cut flowers, bulbs, tropical plants, pot plants, bedding plants and perennials. For our Research department in De Lier we are looking for a Project Lead Artificial Intelligence & Data Science .
Our organization grows and flourishes. This results in a fast-changing and, therefore, challenging environment.
As a Project Lead Artificial Intelligence and Data Science you strengthen the R&D Trait Genetics group. With your solid background in bioinformatics you lead projects on the design of algorithms and pipelines using high throughput phenotyping methods like imaging data. You finalize these pipelines into solutions for our global breeding and research programs. In addition, you are responsible for setting up, developing and maintaining the IT solutions for our Trait Genetics team. As Project Lead, you build and maintain an important network of external and internal collaborations with domain experts in the fields of Trait Genetics, Trait Discovery, Plant Physiology, Phytopathology and Breeding. You will report to the Technology Lead Trait Genetics in the Breeding Technology Centre in De Lier.
Your tasks and responsibilities
• Design, improve and maintain innovative software solutions for large data challenges within the global Dümmen Orange R&D portfolio.
• Initiate and lead projects on developing pipelines for computer vision (preprocessing, segmentation, machine learning, deep learning, etc) and data science, which feed into genomic analyses and molecular breeding applications.
• Make tools and pipelines available for breeding application through automation or for end-users through web-apps or Notebooks.
• Perform scouting activities for novel tools and technologies.
• Build and maintain and internal and external network of collaborations.
• PhD in a relevant field in computer science or biology with a strong computational focus (for example bioinformatics, data science) and preferably >2 years experience in industry.
• You have a thorough understanding of the Linux operating system and are proficient in coding in Python and R (other programming languages are nice to have).
• Proven experience in advanced computer vision applications preferably using various deep learning approaches.
• Prior knowledge of plant biology is not essential, but affinity with plant breeding and quantitative genetics is desirable.
• Experience with DevOps (Kubernetes, Docker), databases (SQL), pipeline tools and workflow management (Snakemake) and cloud computing is desirable.
• Experience with web-apps such as Dash and RShiny is preferred.
• Ability to work independently as well as in fast-paced multidisciplinary teams.
• Inquisitive, innovative and critical mind-set and a creative and pro-active attitude.
• Excellent written and oral communication skills which are tailored to the target audience.
• Excellent command of English and willingness to learn Dutch.
Dümmen Orange has great global ambitions. Innovation, technology and quality are high priorities. This results in a challenging working environment in which you can develop yourself. Dümmen Orange offers its employees plenty of room for personal growth and development. We have an informal and easy accessible working environment in which cooperation is very important.
Dümmen Orange is the world’s largest breeder and propagator of flowers and plants. Its annual turnover is about 350 million euro. The company employs over 7.300 employees worldwide. In addition to a large marketing and sales network, Dümmen Orange has a diversified network of specialized production sites. The key to Dümmen Orange’s success is a broad and deep product range, supported by a global supply chain. The company embraces its social responsibilities and invests in the health, safety and personal development of its staff.
Click on the button below to apply for this job. If you have questions about the job, you can contact Camillo Berenos (Technology Lead Trait Genetics), via +31 174 530 100.
Acquisition with reference to this advertisement will not be appreciated.
An assessment can be part of the recruitment process.