Positions available: Iconix Pharmaceuticals

[Ajay Jain]

*****  PLEASE FORWARD TO RELEVANT MAILING LISTS *****

I am seeking one or two individuals for PhD-level scientist positions at
Iconix Pharmaceuticals.  People with applied neural network experience are
particularly of interest (see details below).

Iconix is a San Francisco Bay Area biopharmaceutical company that is
establishing the new area of Chemical Genomics.   The company's approach
aims to advance the discovery process for human drugs through the
systematic acquisition, integration, and analysis of genetic and chemical
information.

We are seeking people to develop and implement new algorithms for
interpreting large, complex data sets generated from the interaction of
many small molecules with numerous gene products.  Ideal candidates will
have a PhD in computer science and demonstrated success in applying
sophisticated computation to real-world problems (e.g. drug discovery,
computational biology, object recognition, robotics, etc.).  Experience in
machine-learning, computational geometry, or physical modeling is
beneficial, as is formal training in chemistry, biology, or physics. 
Experience in applying neural network techniques to problems  involving 
noisy data is particularly relevant.  As the member of an
interdisciplinary team, you will develop, implement, and apply novel
algorithms to the interpretation of chemical and biological information.

Candidates for these positions will have excellent communication skills,
excellent work history and references, and the ability to work both
independently and as part of a multidisciplinary team of scientists,
including colleagues from biology, chemistry, genetics, and other fields.

We offer competitive salaries, stock options, and excellent benefits.
Please send or fax your resume to: Human Resources Dept., Iconix
Pharmaceuticals, Inc., 850 Maude Avenue, Mountain View, CA 94043.
Attn: Chemical Information Sciences Group.  FAX (650) 526-3034, EMAIL
hr at iconixpharm.com.  Iconix Pharmaceuticals, Inc., is an Equal
Opportunity Employer.

The type of research involved is exemplified by the following papers:

J. Ruppert, W. Welch, and A. N. Jain. Automatic Characterization and
Identification of Protein Binding Pockets for Molecular Docking. Protein
Science 6: 524-533, 1996.

A. N. Jain. Scoring Non-Covalent Ligand-Protein Interactions: A Continuous
Differentiable Function Tuned to Compute Binding Affinities. Journal of
Computer-Aided Molecular Design. 10:5, 427-440, 1996.

W. Welch, J. Ruppert, and A. N. Jain. Hammerhead: Fast, Fully Automated
Docking of Flexible Ligands to Protein Binding Sites. Chemistry and
Biology 3: 449-462, 1996.

A. N. Jain, N. L. Harris, and J. Y. Park. Quantitative Binding Site Model
Generation: Compass Applied to Multiple Chemotypes Targeting the 5HTlA
Receptor. Journal of Medicinal Chemistry 38: 1295-1307, 1995.

A. N. Jain, T. G. Dietterich, R. L. Lathrop, D. Chapman, R. E. Critchlow,
B. E. Bauer, T. A. Webster, and T. Lozano-Perez. Compass: A Shape-Based
Machine Learning Tool for Drug Design. Journal of Computer-Aided Molecular
Design 8(6): 635-652, 1994.

A. N. Jain, K. Koile, D. Chapman. Compass: Predicting Biological
Activities from Molecular Surface Properties; Performance Comparisons on a
Steroid Benchmark. Journal of Medicinal Chemistry 37: 2315-2327, 1994.

T. G. Dietterich, A. N. Jain, R. L. Lathrop, and T. Lozano-Perez. A
Comparison of Dynamic Reposing and Tangent Distance for Drug Activity
Prediction. In Advances in Neural information Processing Systems 6, ed. J.
D. Cowan, G. Tesauro, and J. Alspector. San Francisco, CA: Morgan Kaufmann.
 1994.


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Dr. Ajay N. Jain   Associate Director, Chemical Information Sciences
850 Maude Ave.                                Iconix Pharmaceuticals
Mountain View, CA 94043                        ajain at iconixpharm.com