We are seeking a highly skilled and motivated Data Scientist with 
background in computational biology, biophysics, bioinformatics or 
computational chemistry to join our innovative team. The successful 
candidate will focus on developing and maintaining deep learning models 
in natural language processing and/or graph neural networks such as link 
prediction and other machine learning tasks to develop drug discovery 
tools. This role requires a deep understanding of machine learning, deep 
learning, and graph-related models. The candidate will leverage 
state-of-the-art architectures, including various open-source 
transformer-based models. 

Responsibilities:
- Design and implement advanced machine learning models and algorithms 
to solve complex business problems.
- Develop and optimize models for tasks such as link prediction, entity 
recognition, and relation extraction.
- Engage in end-to-end development, from data preprocessing, model 
training, and evaluation to deployment in production.
- Contribute to developing and fine-tuning large language models (LLMs), 
integrating them into our existing frameworks.
- Collaborate with cross-functional teams to integrate models into 
production environments, including data engineers, software developers, 
and domain experts.
- Perform rigorous evaluation and experimentation to ensure model 
accuracy and robustness.
- Stay current with the latest research in machine learning, deep 
learning, graph neural network models, and NLP to continuously improve 
model performance.
- Document model development processes and experimental results and 
maintain code repositories using best practices in version control.

Basic Qualifications:
- PhD in computational biology, biophysics, or computational chemistry.
- 2+ years of experience in developing machine learning models and 
algorithms.
- Proficiency in Python and experience with machine learning frameworks 
such as TensorFlow, PyTorch, or similar.
- Strong knowledge of graph theory and experience with graph-based models 
and algorithms.
- Proven experience with large language models (LLMs) and familiarity with 
various open-source transformer-based architectures.
- Excellent understanding of algorithms, data structures, and complexity 
analysis.
- Strong analytical and problem-solving skills, with a keen attention to 
detail.
- Ability to work independently and collaboratively within a team setting.

Preferred Qualifications:
- Experience with cloud computing platforms such as AWS, GCP, or Azure.
- Advanced knowledge of statistical analysis and data visualization tools, 
such as R, SAS, or Matplotlib.
- Experience with natural language processing (NLP) techniques and 
applications.
- Familiarity with version control systems, particularly Git.
- Understanding of MLOps principles and best practices for deploying 
machine learning models in production environments.
- Experience in feature engineering, model selection, and hyperparameter 
tuning.
- Strong publication record in machine learning, data science, or related 
fields, including contributions to conferences and journals.
- Excellent communication skills, with the ability to explain complex 
technical concepts to non-technical stakeholders.
- Experience as a prompt engineer, including crafting and optimizing 
prompts for LLMs to improve model performance and relevance.

This is a remote position; however, candidates must be legally authorized 
to work and receive a salary in the United States. This includes 
individuals on OPT, H-1B visas, or other valid work authorizations.

Please send your CV in a PDF file to Ms. Yi Wu (wuy[*]insilicom.com). In 
your email, please clearly address the following questions:

1) Do you hold a PhD degree in computational biology, biophysics, or 
computational chemistry?
2) Do you have over 2 years of experience developing machine learning 
models and algorithms?
3) Are you proficient in Python, and do you have experience with machine 
learning frameworks such as TensorFlow, PyTorch, or similar tools?
4) Are you legally authorized to work in the United States? This includes 
individuals on OPT, H-1B visas, or other valid work authorizations.

Applications will be reviewed on a rolling basis, and early submissions 
are strongly encouraged, as we aim to begin the review and decision-making 
process as soon as possible.