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- Aufgaben: Develop ML models and apply uncertainty estimation methods for molecular property predictions.
- Arbeitgeber: Join a cutting-edge team in Basel focused on cheminformatics and data science.
- Mitarbeitervorteile: Gain hands-on experience in a multidisciplinary environment with potential for remote work.
- Warum dieser Job: Perfect for those passionate about machine learning and making an impact in life sciences.
- Gewünschte Qualifikationen: MSc in a quantitative field, strong stats knowledge, and expert Python skills required.
- Andere Informationen: Opportunity to present findings to diverse audiences and enhance your communication skills.
Job Description SummaryMachine learning/Data science internship to work with predictive modeling and uncertainty estimation in the context of molecular property prediction and cheminformatics.Job DescriptionDuration: 6 monthsStart: as soon as possibleLocation: Campus BaselMajor accountabilities:Develop ML models for compound property predictionsImplement, apply and benchmark uncertainty estimation methods for ML modelsWork in a multidisciplinary environmentPresent project outcomes to technical and non-technical audiencesMinimum Requirements:MSc in a quantitative field or life sciences, preferably with multidisciplinary background (cheminformatics, bioinformatics, biomedical data science)Strong understanding of statistics and experience with machine learning / deep learningExpert knowledge of PythonExperience with reproducible data science tools and practicesExcellent communication skills and ability to translate analytical concepts for diverse audience and stakeholders (English is our primary language)Desired:Previous research experience either in academia or industryExperience with uncertainty quantificationKnowledge of explainable AISkills:PythonStatistics, machine learning, deep learning, predictive modelingLanguages:English #J-18808-Ljbffr
Machine Learning Intern Arbeitgeber: Healthcare Businesswomen’s Association
Kontaktperson:
Healthcare Businesswomen’s Association HR Team
StudySmarter Bewerbungstipps 🤫
So bekommst du den Job: Machine Learning Intern
✨Tip Number 1
Make sure to showcase your experience with Python and machine learning in your conversations. Be ready to discuss specific projects where you've implemented ML models or worked with predictive modeling.
✨Tip Number 2
Familiarize yourself with uncertainty estimation methods and be prepared to explain how they can be applied in molecular property prediction. This will demonstrate your understanding of the field and your ability to contribute.
✨Tip Number 3
Practice explaining complex statistical concepts in simple terms. Since you'll be presenting to both technical and non-technical audiences, being able to communicate effectively is key.
✨Tip Number 4
Engage with the latest research in cheminformatics and bioinformatics. Showing that you are up-to-date with current trends and methodologies can set you apart from other candidates.
Diese Fähigkeiten machen dich zur top Bewerber*in für die Stelle: Machine Learning Intern
Tipps für deine Bewerbung 🫡
Understand the Role: Make sure to thoroughly read the job description for the Machine Learning Intern position. Understand the key responsibilities and required skills, especially focusing on machine learning, statistics, and Python expertise.
Tailor Your CV: Customize your CV to highlight relevant experiences in machine learning, data science, and any projects related to cheminformatics or bioinformatics. Emphasize your programming skills in Python and any experience with reproducible data science practices.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for machine learning and your understanding of its applications in molecular property prediction. Mention specific projects or experiences that align with the internship's requirements.
Highlight Communication Skills: Since excellent communication skills are essential, provide examples in your application where you successfully translated complex analytical concepts to non-technical audiences. This will demonstrate your ability to present project outcomes effectively.
Wie du dich auf ein Vorstellungsgespräch bei Healthcare Businesswomen’s Association vorbereitest
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and machine learning. Bring examples of projects you've worked on, especially those involving predictive modeling or uncertainty estimation.
✨Communicate Clearly
Since you'll need to present complex concepts to both technical and non-technical audiences, practice explaining your work in simple terms. This will demonstrate your excellent communication skills.
✨Highlight Relevant Experience
If you have previous research experience, whether in academia or industry, make sure to mention it. Discuss how it relates to the role and what you learned from those experiences.
✨Prepare for Behavioral Questions
Expect questions about teamwork and working in multidisciplinary environments. Think of examples that showcase your ability to collaborate and adapt to different perspectives.
