Computer Vision Engineer - Machine Learning
Rozzano, IT, 20089
Humanitas Research Hospital
Humanitas promuove la salute, la prevenzione e la diagnosi precoce attraverso attività ambulatoriali e servizi avanzati e innovativi.We are looking for a Computer Vision Engineer with at least 3 years of experience in computer vision applied to medical imaging field. As part of our Computer Vision team we expect the candidate to help us discover the information hidden in radiological and general medical image data, and help us make smart decisions to deliver even better clinical services.
As a senior member of the Computer Vision engineering team, we expect you to contribute in performing exploratory analysis, applying data mining techniques, doing statistical and radiomics analysis, building AI-based models and products such as prediction systems, classification and detection tools.
You will be part of the Humanitas AI Center and report to the Chief Innovation Officer.
The AI Center of Humanitas is focused in research in the field of Artificial Intelligence applied in healthcare. Research and development areas include predictive and decision-support systems based on data-driven model (ML/DL models) to optimize clinical processes and ultimately improve the quality of patient care. We are a team of multidisciplinary scientists who work day by day on e-health and AI projects, by collaborating with clinical staff (doctors, nurses, researchers) and management staff.
Responsibilities- Development of machine learning and deep learning models on images and/or 3D/time-variant data;
- Contribute to solutions design and establishment of requirements;
- Retrieval and querying of data from distributed architecture databases;
- Exploratory data analysis on clinical data and integration of highly fragmented data;
- Self and team-management on individual and team-sized studies’ deadlines;
- Data visualization and effective results reporting;
- Deriving knowledge and decisions support using data-driven approaches.
- Fluent in written and spoken English and Italian;
- At least 3 years of experience in computer vision applied to medical imaging field (e.g. CT, MRI, CR, DTS, Digital Pathology, etc.);
- Excellent understanding of Deep Learning models and their applications to image classification, image segmentation and object detection; experience with visual-language models would be a plus.
- Experienced knowledge of Machine Learning techniques and algorithms, such as k-NN, Naive Bayes, Support Vector Machines, Random Forests, etc;
- Good applied statistics skills, such as distributions, statistical testing, regression, etc;
- Advanced proficiency in Python
- Advanced scripting and programming skills;
- Experience with cloud (GCP, AWS) and/or distributed computing;
- Experienced knowledge of SQL is appreciated;
- Experience with data science frameworks: tensorflow, pytorch, scikit-learn, scipy, pandas, numpy;
- Experience with visualization frameworks: plotly, seaborn, matplotlib;
- Master (PhD would be a plus) in a STEM discipline.
Soft Skills
- Excellent team-working capabilities even with colleagues from different research areas and backgrounds;
- Strong self-motivation, commitment and proactive approach;
- Ability to meet deadlines and work autonomously in rapidly changing environments;
- Curiosity and ability of stepping outside your comfort zone.
Contract and duration
We can offer a fixed-term contract. Contract duration, salary, as well as employment level, will be defined based on candidate's profile.
All candidate data collected from the application shall be processed in accordance with applicable law: Dlgs 198/2006 e dei Dlgs 215/2003 e 216/2003; privacy ex artt. 13 e 14 del Reg. UE 2016/679.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Architecture AWS Classification Computer Vision Data analysis Data Mining Data visualization Deep Learning EDA Engineering GCP Machine Learning Matplotlib NumPy Pandas PhD Plotly Privacy Python PyTorch Research Scikit-learn SciPy Seaborn SQL Statistics STEM TensorFlow Testing
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