Recruit Detail
Company Name
Knowledge Palette Co., Ltd.
Occupation
Computational Life Science Field (Machine Learning Engineer/Data Scientist)
Work Detail
In the pharmaceutical industry, where the time and cost of developing new drugs is increasing year by year, advances in AI technologies such as machine learning and deep learning, as well as improvements in data processing speed by computers, are expected to play a major role in solving these issues. In fact, decisive changes are being brought about, such as shortening the drug discovery process and significantly improving the probability of development. At our company, we are acquiring cell big data with a unique approach of ``manipulating cells with big data extracted from cells and leading to the creation of new drugs.'' We are looking for researchers who are motivated by a wide range of research and development, from basics to applications, and who can promote the development of machine learning and data analysis technologies for the creation of new drugs and the practical application of regenerative medicine. We are able to analyze and apply large-scale, high-precision cellular big data, which is only possible because we are a company that develops cutting-edge experiment and analysis technology. Specifically, through in-house research and joint research, we are developing a wide variety of machine learning algorithms, including the following. ・Use (semi-)supervised learning to analyze the types and proportions of cells contained in cell samples at the single-cell level, and identify cells and genes related to disease mechanisms and drug targets. ・Use causal inference algorithms to estimate gene regulatory networks and understand the principles of cell activity and disease development factors. ・Use Bayesian optimization to create experimental plans to optimize cell culture conditions and manufacturing processes for regenerative medicine products. ・Use segmentation to extract the shape of individual cells from microscopic images and evaluate cell culture conditions and shape responsiveness to drugs. We are looking for people who can improve and advance these tasks. In addition to these duties, we are also looking for individuals who can proactively propose new analysis methods using internal and external data, and who can create new value that will lead to the practical application of drug discovery and regenerative medicine. . Depending on suitability, etc., we may order you to transfer to work specified by the company.
Ideal Profile
Required skills ・Basic knowledge of machine learning and statistical models (linear models, loss functions, cross validation, etc.) ・Over 1 year of research and development experience using machine learning/statistical models (library development, data analysis, CI/CD, paper writing, conference presentations, etc.) ・Familiarity with deep learning frameworks (PyTorch/Keras/TensorFlow, etc.) welcome skills ・Familiarity with the latest deep learning architectures (Transformer/Diffusion model/VAE, etc.) ・Natural language processing knowledge and experience (LLM/Chat GPT/Large-scale language model/Time series model) ・Team management experience ・Interest and desire to learn in the life science field (medicine, pharmacy, biology, etc.) ・Familiarity with XAI (Explainable AI) (SHAP/LIME/Anchors, etc.) ・Experience and achievements in competitions (Kaggle/SIGNATE/AtCoder, etc.)
Work Location
Either Nihonbashi Office or Kobe Research Institute *Remote work can be combined, full remote work is possible depending on experience Please note that we may order you to transfer to a business location designated by the company (including reassignment that involves relocation).
Phd. Stating Salary
Annual income of 6-12 million yen or more *Determined based on experience, ability, age, etc. Salary increase once a year, overtime pay
Selection Flow
Apply Click the "Apply" button on each position page above, enter the necessary information, and apply. ↓ Document screening: Screening will be based on the submitted documents. Regardless of whether you pass or fail, you will be notified of the results by email within a week or so. Successful candidates will be informed of the interview schedule. ↓ Interview During the interview, we will explain our business and discuss the job you will be responsible for. We also ask for a presentation from the candidate (self-introduction, motivation for applying, past experience, and personal skills). There will also be time for a question and answer session, so please ask if you have any questions. Regardless of whether you pass or fail, you will be notified of the results by email within a week or so. *Interviews will be conducted multiple times. *Conducted online or in person *You may be asked to submit additional documents, etc. ↓ A notice of offer will be sent to those who pass the final interview.