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Company Name

Knowledge Palette Co., Ltd.

Job Type

Computational Life Sciences (Machine Learning Engineer/Data Scientist)

Work Detail

In the pharmaceutical industry, where the time and cost of new drug development are increasing year by year, the development of AI technologies such as machine learning and deep learning, and the improvement of computer data processing speed, are expected to play a major role in solving these challenges. In fact, decisive changes such as shortening the drug discovery process and significantly improving the success rate of development are already being brought about. Our company is pursuing a unique approach of "manipulating cells with big data extracted from cells to create new drugs," and is acquiring cellular big data. We are seeking researchers who are motivated by a wide range of research and development, from basic to applied, and who can promote the development of machine learning and data analysis technologies for new drug discovery and the practical application of regenerative medicine. Because we develop cutting-edge experimental and analytical technologies, we can analyze and apply large-scale, high-precision cellular big data that is only possible to acquire at our company. Specifically, in our in-house research and collaborative research, we are developing a wide variety of machine learning algorithms, such as the following: We are looking for someone who can continuously refine and advance these tasks. In addition, we are seeking someone who can proactively propose novel analytical methods using internal and external data, creating new value that leads to the practical application of drugs and regenerative medicine. Depending on aptitude and other factors, you may be assigned to a different role. You may be assigned to a different role depending on your aptitude. Depending on your aptitude, you may be assigned to a different role. Your role may be transferred to a different role as instructed by the company. * Bayesian optimization may be used to optimize cell culture conditions and manufacturing processes for regenerative medicine products. * Bayesian optimization may be used to optimize cell culture conditions and manufacturing processes for regenerative medicine products. Depending on your aptitude and other factors, you may be assigned to a different role as instructed by the company.

Ideal Profile

Required Skills * Basic knowledge of machine learning and statistical models (linear models, loss functions, cross-validation, etc.) * At least one year of research and development experience using machine learning and statistical models (library development, data analysis, CI/CD, paper writing, conference presentations, etc.) * Proficiency in deep learning frameworks (PyTorch/Keras/TensorFlow, etc.) Preferred Skills * Proficiency in the latest deep learning architectures (Transformer/Diffusion models/VAE, etc.) * Knowledge and experience in natural language processing (LLM/Chat GPT/Large-scale language models/Time series models) * Team management experience * Interest in and willingness to learn about the life sciences field (medicine, pharmacy, biology, etc.) * Proficiency in XAI (Explainable AI) (SHAP/LIME/Anchors, etc.) * Experience and achievements in competitions (Kaggle/SIGNATE/AtCoder, etc.)

Work Location

Either the Nihonbashi office or the Kobe research institute. *Remote work is possible in combination with other work arrangements; full remote work is possible depending on experience. Please note that you may be ordered to transfer to a company-designated office (including relocation requiring a change of residence).

Phd. Stating Salary

Annual salary of 6-12 million yen or more (determined based on experience, skills, age, etc.) Annual salary increase, overtime pay

Selection Flow

Application: Click the "Apply" button on each position page above, fill in the required information, and submit your application. ↓ Document Screening: We will review your application based on the documents you submit. We will notify you of the results, whether successful or unsuccessful, by email within approximately one week. Those who pass the screening will be notified of the interview schedule. ↓ Interview: During the interview, we will discuss our business and the job responsibilities you will be responsible for. We will also ask you to give a presentation (self-introduction, reasons for applying, past experience and skills). There will be a Q&A session, so please feel free to ask any questions. We will notify you of the results, whether successful or unsuccessful, by email within approximately one week. *Multiple interviews will be conducted. *Interviews will be conducted online or in person. *Additional documents may be requested. ↓ Job Offer: We will send a job offer notification to those who pass the final interview.

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